Los datos empleados pertenecen al “Hepatitis C Virus (HCV) for Egyptian patients” de la UCI Machine Learning Repository en el enlace https://archive-beta.ics.uci.edu/dataset/503/hepatitis+c+virus+hcv+for+egyptian+patients. En nuestro caso los datos se encuentran en el archivo HCV-Egy-Data.csv.
Este conjunto de datos corresponde al análisis de varias características útiles para determinar los grados de fibrosis hepática (FH). Desde el enlace al repositorio de la UCI podemos observar una descripción de los atributos:
| Variables | Descripción |
|---|---|
| Age | Edad del paciente |
| Gender | Sexo del paciente |
| BMI | Índice de masa corporal |
| Fever | Fiebre |
| Nausea/Vomiting | Nausea o vómito |
| Headache | Dolor de cabeza |
| Diarrhea | Diarrea |
| Fatigue/Bone ache | Fatiga generalizada/Dolor de huesos |
| Jaundice | Ictericia |
| Epigastria pain | Dolor epigastrico |
| WBC | Leucocitos |
| RBC | Globulos rojos |
| HGB | Hemoglobina |
| Plat | Plaquetas |
| AST.1 | Aspartato aminotrasferasa de 1 semana |
| ALT.1 | Alanina transaminasa de 1 semana |
| ALT.4 | Alanina transaminasa de 4 semanas |
| ALT.12 | Alanina transaminasa de 12 semanas |
| ALT.24 | Alanina transaminasa de 24 semanas |
| ALT.36 | Alanina transaminasa de 36 semanas |
| ALT.48 | Alanina transaminasa de 48 semanas |
| ALT.after.24.w | Alanina transaminasa después de 48 semanas |
| RNA.Base | RNA Base |
| RNA.4 | RNA 4 semanas |
| RNA.12 | RNA 12 semanas |
| RNA.EOT | RNA al finalizar el tratamiento |
| RNA.EF | RNA Factor de elongación |
| Baseline.histological.Grading | Clasificación histológica de referencia |
| Baselinehistological.staging | Estadificación histológica |
Tras tener una idea general que cuales son los datos del fichero HCV-Egy-Data.csv procedemos a cargar, explorar y preparar los datos:
# Cargamos los datos
HCV <- read.csv(file.path(params$folder.data,params$myfile), header=TRUE)
Exploramos los datos y los preparamos para realizar los análisis posteriores. Primero nombramos correctamente las columnas/variables del conjunto de datos.
# Nombramos correctamente las columnas del conjunto de datos
variables <- c("Age","Gender","BMI","Fever","Nausea.Vomiting","Headache","Diarrhea","Fatigue.Boneache","Jaundice","Epigastria.pain","WBC","RBC","HGB","Plat","AST.1","ALT.1","ALT.4","ALT.12","ALT.24","ALT.36","ALT.48","ALT.after.24.w","RNA.Base","RNA.4", "RNA.12", "RNA.EOT","RNA.EF","BH.grading", "BH.staging")
colnames(HCV) <- variables
El conjunto de datos HCV está formado por 29 variables con 1385 registros y no contiene valores NA, por tanto no tenemos valores faltantes. Mostramos los primeros 6 registros del conjunto HCV para familiarizarnos con los datos:
| Age | Gender | BMI | Fever | Nausea.Vomiting | Headache | Diarrhea | Fatigue.Boneache | Jaundice | Epigastria.pain | WBC | RBC | HGB | Plat | AST.1 | ALT.1 | ALT.4 | ALT.12 | ALT.24 | ALT.36 | ALT.48 | ALT.after.24.w | RNA.Base | RNA.4 | RNA.12 | RNA.EOT | RNA.EF | BH.grading | BH.staging |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 56 | 1 | 35 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 7425 | 4248807 | 14 | 112132 | 99 | 84 | 52 | 109 | 81 | 5 | 5 | 5 | 655330 | 634536 | 288194 | 5 | 5 | 13 | 2 |
| 46 | 1 | 29 | 1 | 2 | 2 | 1 | 2 | 2 | 1 | 12101 | 4429425 | 10 | 129367 | 91 | 123 | 95 | 75 | 113 | 57 | 123 | 44 | 40620 | 538635 | 637056 | 336804 | 31085 | 4 | 2 |
| 57 | 1 | 33 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 4178 | 4621191 | 12 | 151522 | 113 | 49 | 95 | 107 | 116 | 5 | 5 | 5 | 571148 | 661346 | 5 | 735945 | 558829 | 4 | 4 |
| 49 | 2 | 33 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 6490 | 4794631 | 10 | 146457 | 43 | 64 | 109 | 80 | 88 | 48 | 77 | 33 | 1041941 | 449939 | 585688 | 744463 | 582301 | 10 | 3 |
| 59 | 1 | 32 | 1 | 1 | 2 | 1 | 2 | 2 | 2 | 3661 | 4606375 | 11 | 187684 | 99 | 104 | 67 | 48 | 120 | 94 | 90 | 30 | 660410 | 738756 | 3731527 | 338946 | 242861 | 11 | 1 |
| 58 | 2 | 22 | 2 | 2 | 2 | 1 | 2 | 2 | 1 | 11785 | 3882456 | 15 | 131228 | 66 | 104 | 121 | 96 | 65 | 73 | 114 | 29 | 1157452 | 1086852 | 5 | 5 | 5 | 4 | 4 |
Comprobamos la estructura de las variables y observamos que tenemos
variables categóricas y numéricas, las variables Gender,
Fever, Nausea.Vomiting, Headache,
Diarrhea, Fatigue.Bone ache,
Jaundice, Epigastria.pain,
BH.grading, BH.staging son numéricas pero
deben ser categóricas, por tanto deben ser transformadas a factor ya que
es el objeto de R adecuado.
# Estructura del conjunto de datos:
str(HCV)
'data.frame': 1385 obs. of 29 variables:
$ Age : int 56 46 57 49 59 58 42 48 44 45 ...
$ Gender : int 1 1 1 2 1 2 2 2 1 1 ...
$ BMI : int 35 29 33 33 32 22 26 30 23 30 ...
$ Fever : int 2 1 2 1 1 2 1 1 1 2 ...
$ Nausea.Vomiting : int 1 2 2 2 1 2 1 1 1 1 ...
$ Headache : int 1 2 2 1 2 2 2 2 2 2 ...
$ Diarrhea : int 1 1 2 2 1 1 2 2 2 2 ...
$ Fatigue.Boneache: int 2 2 1 1 2 2 2 1 2 1 ...
$ Jaundice : int 2 2 1 2 2 2 2 1 1 1 ...
$ Epigastria.pain : int 2 1 1 1 2 1 2 2 2 2 ...
$ WBC : int 7425 12101 4178 6490 3661 11785 11620 7335 10480 6681 ...
$ RBC : num 4248807 4429425 4621191 4794631 4606375 ...
$ HGB : int 14 10 12 10 11 15 12 11 12 12 ...
$ Plat : num 112132 129367 151522 146457 187684 ...
$ AST.1 : int 99 91 113 43 99 66 78 119 93 55 ...
$ ALT.1 : int 84 123 49 64 104 104 57 112 83 68 ...
$ ALT.4 : num 52 95 95 109 67 121 113 80 55 72 ...
$ ALT.12 : int 109 75 107 80 48 96 118 127 102 127 ...
$ ALT.24 : int 81 113 116 88 120 65 107 45 97 81 ...
$ ALT.36 : int 5 57 5 48 94 73 84 96 122 125 ...
$ ALT.48 : int 5 123 5 77 90 114 80 53 39 43 ...
$ ALT.after.24.w : int 5 44 5 33 30 29 28 39 45 30 ...
$ RNA.Base : int 655330 40620 571148 1041941 660410 1157452 325694 641129 591441 1151206 ...
$ RNA.4 : int 634536 538635 661346 449939 738756 1086852 1034008 72050 757361 230488 ...
$ RNA.12 : int 288194 637056 5 585688 3731527 5 275095 787295 5 267320 ...
$ RNA.EOT : int 5 336804 735945 744463 338946 5 214566 370605 371090 275295 ...
$ RNA.EF : int 5 31085 558829 582301 242861 5 635157 506296 203042 555516 ...
$ BH.grading : int 13 4 4 10 11 4 12 12 5 4 ...
$ BH.staging : int 2 2 4 3 1 4 4 3 2 2 ...
La variable Gender (Género) debería ser categórica con
dos niveles, Male (Masculino), Female (Femenino), por
lo que tenemos que codificarla correctamente.
# Variable class es un factor con dos niveles:
HCV$Gender <- factor(HCV$Gender, levels = c(1,2), labels = c("Male","Female"))
Transformamos las variables Fever,
Nausea.Vomiting, Headache,
Diarrhea, Fatigue.Boneache,
Jaundice, Epigastria.pain, las cuales son
categóricas con dos niveles, Absent (Ausente), Present
(Presente).
# Variable class es un factor con dos niveles:
HCV$Fever <- factor(HCV$Fever, levels = c(1,2), labels = c("Absent","Present"))
HCV$Nausea.Vomiting <- factor(HCV$Nausea.Vomiting, levels = c(1,2), labels = c("Absent","Present"))
HCV$Headache <- factor(HCV$Headache, levels = c(1,2), labels = c("Absent","Present"))
HCV$Diarrhea <- factor(HCV$Diarrhea, levels = c(1,2), labels = c("Absent","Present"))
HCV$Fatigue.Boneache <- factor(HCV$Fatigue.Boneache, levels = c(1,2), labels = c("Absent","Present"))
HCV$Jaundice <- factor(HCV$Jaundice, levels = c(1,2), labels = c("Absent","Present"))
HCV$Epigastria.pain <- factor(HCV$Epigastria.pain, levels = c(1,2), labels = c("Absent","Present"))
La variable BH.staging refleja los estados de fibrosis
del paciente por tanto deben ser cambiadas a factor ya que de esta forma
nos servirá para la mayoría de algoritmos a emplear. Tiene cinco
niveles: Sin Fibrosis (F0), Fibrosis portal sin septos (F1), Fibrosis
portal con algunos septos (F2), Numerosos septos sin cirrosis (F3) y
cirrosis (F4).
# Variable class es un factor con dos niveles:
HCV$BH.staging <- factor(HCV$BH.staging, levels = c(1,2,3,4), labels = c("F1","F2","F3","F4"))
Comprobamos que los cambios se han efectuado correctamente:
# Estructura del conjunto de datos:
str(HCV)
'data.frame': 1385 obs. of 29 variables:
$ Age : int 56 46 57 49 59 58 42 48 44 45 ...
$ Gender : Factor w/ 2 levels "Male","Female": 1 1 1 2 1 2 2 2 1 1 ...
$ BMI : int 35 29 33 33 32 22 26 30 23 30 ...
$ Fever : Factor w/ 2 levels "Absent","Present": 2 1 2 1 1 2 1 1 1 2 ...
$ Nausea.Vomiting : Factor w/ 2 levels "Absent","Present": 1 2 2 2 1 2 1 1 1 1 ...
$ Headache : Factor w/ 2 levels "Absent","Present": 1 2 2 1 2 2 2 2 2 2 ...
$ Diarrhea : Factor w/ 2 levels "Absent","Present": 1 1 2 2 1 1 2 2 2 2 ...
$ Fatigue.Boneache: Factor w/ 2 levels "Absent","Present": 2 2 1 1 2 2 2 1 2 1 ...
$ Jaundice : Factor w/ 2 levels "Absent","Present": 2 2 1 2 2 2 2 1 1 1 ...
$ Epigastria.pain : Factor w/ 2 levels "Absent","Present": 2 1 1 1 2 1 2 2 2 2 ...
$ WBC : int 7425 12101 4178 6490 3661 11785 11620 7335 10480 6681 ...
$ RBC : num 4248807 4429425 4621191 4794631 4606375 ...
$ HGB : int 14 10 12 10 11 15 12 11 12 12 ...
$ Plat : num 112132 129367 151522 146457 187684 ...
$ AST.1 : int 99 91 113 43 99 66 78 119 93 55 ...
$ ALT.1 : int 84 123 49 64 104 104 57 112 83 68 ...
$ ALT.4 : num 52 95 95 109 67 121 113 80 55 72 ...
$ ALT.12 : int 109 75 107 80 48 96 118 127 102 127 ...
$ ALT.24 : int 81 113 116 88 120 65 107 45 97 81 ...
$ ALT.36 : int 5 57 5 48 94 73 84 96 122 125 ...
$ ALT.48 : int 5 123 5 77 90 114 80 53 39 43 ...
$ ALT.after.24.w : int 5 44 5 33 30 29 28 39 45 30 ...
$ RNA.Base : int 655330 40620 571148 1041941 660410 1157452 325694 641129 591441 1151206 ...
$ RNA.4 : int 634536 538635 661346 449939 738756 1086852 1034008 72050 757361 230488 ...
$ RNA.12 : int 288194 637056 5 585688 3731527 5 275095 787295 5 267320 ...
$ RNA.EOT : int 5 336804 735945 744463 338946 5 214566 370605 371090 275295 ...
$ RNA.EF : int 5 31085 558829 582301 242861 5 635157 506296 203042 555516 ...
$ BH.grading : int 13 4 4 10 11 4 12 12 5 4 ...
$ BH.staging : Factor w/ 4 levels "F1","F2","F3",..: 2 2 4 3 1 4 4 3 2 2 ...
Observamos que ahora todas las variables están correctamente guardadas en función de los datos que contienen.
Tras guardar los datos correctamente en R, comprobamos el número de pacientes en cada estado hepático.
| F1 | F2 | F3 | F4 |
|---|---|---|---|
| 336 | 332 | 355 | 362 |
Como podemos observar no existen datos para el estado F0 de FH ya que todos los pacientes de este estudio presentan algún grado de fibrosis.
| F1 | F2 | F3 | F4 |
|---|---|---|---|
| 0.24 | 0.24 | 0.26 | 0.26 |
Observamos que el número de pacientes por cada estado de FH se encuentra balanceado.
Ahora observamos el número de muestras de cada género. En donde encontramos que en el estudio existen más hombre que mujeres con un 3% de diferencia.
| Male | Female |
|---|---|
| 707 | 678 |
| Male | Female |
|---|---|
| 0.51 | 0.49 |
Vamos a estudiar la distribución de la variable respuesta, ya que, es
la variable que nos interesa predecir. Observamos la variable
BH.staging esta balanceada.
Gráfico de barras variable respuesta.
Los modelos predictivos deben de tener un porcentaje de acierto superior a lo esperado por azar o a un determinado nivel basal. En problemas de clasificación, el nivel basal es el que se obtiene si se asignan todas las observaciones a la clase mayoritaria (la moda).
# Porcentaje de aciertos si se predice para todas las observaciones que padecen LD.
n_observaciones <- nrow(HCV)
predicciones <- rep(x = "F4", n_observaciones)
mean(predicciones == HCV$BH.staging) * 100
[1] 26.13718
# porcentaje mínimo que hay que superar con los modelos predictivos
Debido a que los datos están balanceados el porcentaje mínimo que hay que intentar superar con los modelos predictivos es del 26.14%.
Exploramos los datos de las variables continuas. Realizamos un breve resumen estadístico de las variables numéricas del conjunto:
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. | |
|---|---|---|---|---|---|---|
| Age | 32 | 39 | 46 | 46.32 | 54 | 61 |
| BMI | 22 | 25 | 29 | 28.61 | 32 | 35 |
| WBC | 2991 | 5219 | 7498 | 7533.39 | 9902 | 12101 |
| RBC | 3816422 | 4121374 | 4438465 | 4422129.61 | 4721279 | 5018451 |
| HGB | 10 | 11 | 13 | 12.59 | 14 | 15 |
| Plat | 93013 | 124479 | 157916 | 158348.06 | 190314 | 226464 |
| AST.1 | 39 | 60 | 83 | 82.77 | 105 | 128 |
| ALT.1 | 39 | 62 | 83 | 83.92 | 106 | 128 |
| ALT.4 | 39 | 61 | 82 | 83.41 | 107 | 128 |
| ALT.12 | 39 | 60 | 84 | 83.51 | 106 | 128 |
| ALT.24 | 39 | 61 | 83 | 83.71 | 107 | 128 |
| ALT.36 | 5 | 61 | 84 | 83.12 | 106 | 128 |
| ALT.48 | 5 | 61 | 83 | 83.63 | 106 | 128 |
| ALT.after.24.w | 5 | 28 | 34 | 33.44 | 40 | 45 |
| RNA.Base | 11 | 269253 | 593103 | 590951.22 | 886791 | 1201086 |
| RNA.4 | 5 | 270893 | 597869 | 600895.65 | 909093 | 1201715 |
| RNA.12 | 5 | 5 | 234359 | 288753.61 | 524819 | 3731527 |
| RNA.EOT | 5 | 5 | 251376 | 287660.34 | 517806 | 808450 |
| RNA.EF | 5 | 5 | 244049 | 291378.29 | 527864 | 810333 |
| BH.grading | 3 | 6 | 10 | 9.76 | 13 | 16 |
El resumen estadístico de las variables numéricas nos dice que la
distribución de las variables es aparentemente normal debemos analizar
por separado a las variables RNA.12, RNA.EOT,
RNA.EF, en donde la media se separa de la mediana para
comprender cuales son las razones.
Observamos que se puede mejorar la calidad de los datos si normalizamos los mismos. Aplicamos una función de normalización para graficar los datos en la misma escala.
Creamos una función para normalizar los datos en base a mínimos y máximos para que tengan valores entre 0 y 1 y poder observar todos los datos a la misma escala.
Se realiza un gráfico de boxplot para observar la distribución de los datos con escala entre 0 y 1.
Boxplots de las variables numéricas.
Se pueden observar valores atípicos en las variables de
ALT.after.24.w y RNA.12
Tratamiento de valores atípicos
Se analiza cada uno de los valores atípicos y considerando las referencias bibliográficas de las pruebas PCR para detección de Virus de la hepatitis C se considera que estos datos pertenecen a un caso excepcional y no a un error, sin embargo sabemos que los valores atípicos si pueden influir en los modelos de aprendizaje por tanto y considerando que se tiene una cantidad suficiente de datos se eliminaran los outliers para la exploración de datos.
Utilizamos la prueba de Grubbs para detectar un valor atipico en la
variable RNA.12 ya que tenemos una gran cantidad de datos,
esta prueba nos ayuda a detectar un único valor atípico mediante un test
de hipótesis nula la cual establece que no hay valores atípicos en los
datos, con una significancia de valor p = 0.05.
Grubbs test for one outlier
data: mynum$RNA.12
G = 12.06506, U = 0.89475, p-value < 2.2e-16
alternative hypothesis: highest value 3731527 is an outlier
En este caso se rechaza la hipótesis nula, y nos dice que el valor
atípico es de 3731527, el cual procederemos a eliminar en
nuestra base de datos.
Ahora realizamos la prueba para los valores atípicos de la variable
ALT.after.24.w
Grubbs test for one outlier
data: mynum$ALT.after.24.w
G = 4.02036, U = 0.98831, p-value = 0.03839
alternative hypothesis: lowest value 5 is an outlier
Nuevamente se rechaza la hipótesis nula, por tanto procedemos a eliminar los datos con valores atípicos.
Se realiza gráficos de dispersión enfrentando todas las variables numéricas entre sí:
Gráficos de dispersión entre las variables numéricas.
Los cocientes de relación más altos entre las variables son
0.41 y 0.42 de las variables RNA.EOT y
RNA.EF con RNA.12 respectivamente por lo cual
se observa que no existe una correlación entre las variables. Respecto a
la distribución de los datos podemos observar que estos tienen
distribuciones uniformes, excepto por las variables RNA.12,
RNA.EOT y RNA.EF que tienen una asimetría
hacia la derecha.
Gráficos variable Age.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 46.3 | 46 | 32 | 61 |
| F2 | 46.3 | 46 | 32 | 61 |
| F3 | 46.3 | 46 | 32 | 61 |
| F4 | 46.3 | 46 | 32 | 61 |
Test Chi-cuadrado:
Estadístico de prueba = 100.8949
p-valor = 0.1464164
Gráficos variable BMI.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 28.59 | 29 | 22 | 35 |
| F2 | 28.59 | 29 | 22 | 35 |
| F3 | 28.59 | 29 | 22 | 35 |
| F4 | 28.59 | 29 | 22 | 35 |
Test Chi-cuadrado:
Estadístico de prueba = 41.53371
p-valor = 0.3608916
Gráficos variable WBC.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 7538.8 | 7514 | 2991 | 12101 |
| F2 | 7538.8 | 7514 | 2991 | 12101 |
| F3 | 7538.8 | 7514 | 2991 | 12101 |
| F4 | 7538.8 | 7514 | 2991 | 12101 |
Test Chi-cuadrado:
Estadístico de prueba = 3914.194
p-valor = 0.4332662
Gráficos variable RBC.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 4422279 | 4438465 | 3816422 | 5018451 |
| F2 | 4422279 | 4438465 | 3816422 | 5018451 |
| F3 | 4422279 | 4438465 | 3816422 | 5018451 |
| F4 | 4422279 | 4438465 | 3816422 | 5018451 |
Test Chi-cuadrado:
Estadístico de prueba = 4138.969
p-valor = 0.4884442
Gráficos variable HGB.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 12.59 | 13 | 10 | 15 |
| F2 | 12.59 | 13 | 10 | 15 |
| F3 | 12.59 | 13 | 10 | 15 |
| F4 | 12.59 | 13 | 10 | 15 |
Test Chi-cuadrado:
Estadístico de prueba = 16.86688
p-valor = 0.3268846
Gráficos variable Plat.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 158347.2 | 157916 | 93013 | 226464 |
| F2 | 158347.2 | 157916 | 93013 | 226464 |
| F3 | 158347.2 | 157916 | 93013 | 226464 |
| F4 | 158347.2 | 157916 | 93013 | 226464 |
Test Chi-cuadrado:
Estadístico de prueba = 4118.969
p-valor = 0.4577108
Gráficos variable AST.1.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 82.76 | 83 | 39 | 128 |
| F2 | 82.76 | 83 | 39 | 128 |
| F3 | 82.76 | 83 | 39 | 128 |
| F4 | 82.76 | 83 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 253.8403
p-valor = 0.7088866
Gráficos variable ALT.1.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 83.92 | 83 | 39 | 128 |
| F2 | 83.92 | 83 | 39 | 128 |
| F3 | 83.92 | 83 | 39 | 128 |
| F4 | 83.92 | 83 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 278.2291
p-valor = 0.3057136
Gráficos variable ALT.4.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 83.44 | 83 | 39 | 128 |
| F2 | 83.44 | 83 | 39 | 128 |
| F3 | 83.44 | 83 | 39 | 128 |
| F4 | 83.44 | 83 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 236.8042
p-valor = 0.9082989
Gráficos variable ALT.12.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 83.5 | 84 | 39 | 128 |
| F2 | 83.5 | 84 | 39 | 128 |
| F3 | 83.5 | 84 | 39 | 128 |
| F4 | 83.5 | 84 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 261.0173
p-valor = 0.5917102
Gráficos variable ALT.24.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 83.65 | 83 | 39 | 128 |
| F2 | 83.65 | 83 | 39 | 128 |
| F3 | 83.65 | 83 | 39 | 128 |
| F4 | 83.65 | 83 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 268.104
p-valor = 0.4694888
Gráficos variable ALT.36.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 83.28 | 84 | 39 | 128 |
| F2 | 83.28 | 84 | 39 | 128 |
| F3 | 83.28 | 84 | 39 | 128 |
| F4 | 83.28 | 84 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 274.8358
p-valor = 0.3577012
Gráficos variable ALT.48.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 83.8 | 84 | 39 | 128 |
| F2 | 83.8 | 84 | 39 | 128 |
| F3 | 83.8 | 84 | 39 | 128 |
| F4 | 83.8 | 84 | 39 | 128 |
Test Chi-cuadrado:
Estadístico de prueba = 255.0925
p-valor = 0.6894139
Gráficos variable ALT.after.24.w.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 33.5 | 34 | 22 | 45 |
| F2 | 33.5 | 34 | 22 | 45 |
| F3 | 33.5 | 34 | 22 | 45 |
| F4 | 33.5 | 34 | 22 | 45 |
Test Chi-cuadrado:
Estadístico de prueba = 62.84167
p-valor = 0.6856197
Gráficos variable RNA.Base.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 591180.9 | 593103 | 11 | 1201086 |
| F2 | 591180.9 | 593103 | 11 | 1201086 |
| F3 | 591180.9 | 593103 | 11 | 1201086 |
| F4 | 591180.9 | 593103 | 11 | 1201086 |
Test Chi-cuadrado:
Estadístico de prueba = 4143
p-valor = 0.4708002
Gráficos variable RNA.4.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 600412.7 | 595314 | 5 | 1201715 |
| F2 | 600412.7 | 595314 | 5 | 1201715 |
| F3 | 600412.7 | 595314 | 5 | 1201715 |
| F4 | 600412.7 | 595314 | 5 | 1201715 |
Test Chi-cuadrado:
Estadístico de prueba = 4138.994
p-valor = 0.4883351
Gráficos variable RNA.12.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 286679.2 | 234359 | 5 | 810028 |
| F2 | 286679.2 | 234359 | 5 | 810028 |
| F3 | 286679.2 | 234359 | 5 | 810028 |
| F4 | 286679.2 | 234359 | 5 | 810028 |
Test Chi-cuadrado:
Estadístico de prueba = 2993.046
p-valor = 0.5014837
Gráficos variable RNA.EOT.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 287715.2 | 251376 | 5 | 808450 |
| F2 | 287715.2 | 251376 | 5 | 808450 |
| F3 | 287715.2 | 251376 | 5 | 808450 |
| F4 | 287715.2 | 251376 | 5 | 808450 |
Test Chi-cuadrado:
Estadístico de prueba = 2996.029
p-valor = 0.5015711
Gráficos variable RNA.EF.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 291641.7 | 244418 | 5 | 810333 |
| F2 | 291641.7 | 244418 | 5 | 810333 |
| F3 | 291641.7 | 244418 | 5 | 810333 |
| F4 | 291641.7 | 244418 | 5 | 810333 |
Test Chi-cuadrado:
Estadístico de prueba = 3002.071
p-valor = 0.5013494
Gráficos variable BH.grading.
| BH.staging | media | mediana | min | max |
|---|---|---|---|---|
| F1 | 9.76 | 10 | 3 | 16 |
| F2 | 9.76 | 10 | 3 | 16 |
| F3 | 9.76 | 10 | 3 | 16 |
| F4 | 9.76 | 10 | 3 | 16 |
Test Chi-cuadrado:
Estadístico de prueba = 32.03351
p-valor = 0.7777465
Se realiza una tabla resumen de los valores obtenidos.
Boxplots de variables continuas por clase de BH.staging
Hemos normalizado las variables para poder visualizarlas en un solo gráfico, dentro de los gráficos de cajas existen tres variables que tienen una distribución distinta como también los hemos observado en el gráfico de densidad, se consideran una distribución uniforme truncada hacia la izquierda, sin embargo ya que se realizado el Test Chi-cuadrado cuyo p-valor nos indica que se acepta la hipótesis nula, asegurando que mantienen una distribución uniforme.
En total tenemos 8 variables cualitativas.
Gráficos variable Gender.
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Male | 0.24 | 0.26 | 0.23 | 0.27 |
| Female | 0.24 | 0.22 | 0.29 | 0.25 |
Gráficos variable Fever.
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.23 | 0.24 | 0.25 | 0.28 |
| Present | 0.25 | 0.24 | 0.26 | 0.24 |
Gráficos variable Nausea.Vomiting.
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.26 | 0.25 | 0.24 | 0.25 |
| Present | 0.22 | 0.23 | 0.27 | 0.27 |
Gráficos variable Headache
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.24 | 0.24 | 0.26 | 0.26 |
| Present | 0.25 | 0.24 | 0.25 | 0.26 |
Gráficos variable Diarrhea
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.23 | 0.25 | 0.26 | 0.26 |
| Present | 0.25 | 0.23 | 0.25 | 0.26 |
Gráficos variable Fatigue.Boneache
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.25 | 0.23 | 0.27 | 0.25 |
| Present | 0.23 | 0.25 | 0.25 | 0.27 |
Gráficos variable Jaundice
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.26 | 0.22 | 0.26 | 0.25 |
| Present | 0.23 | 0.26 | 0.25 | 0.27 |
Gráficos variable Epigastria.pain
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| Absent | 0.21 | 0.25 | 0.27 | 0.27 |
| Present | 0.27 | 0.23 | 0.24 | 0.26 |
Como se puede observar en los gráficos y las proporciones en las tablas son semejantes entre los grupos, por tanto no se sospecha de alguna diferencia estadísticamente significativa entre los mismos.
Buscaremos las relaciones que puedan existir entre las variables
Correlación entre variables continuas
Considerando que la distribución de las variables es uniforme utilizaremos para la correlación el método de Spearman.
# Crear matriz de correlación
corr_mat <- cor(x = mynum.norm, method = "spearman")
colnames(corr_mat) <- names(mynum.norm)
# Crear corrplot con etiquetas de título y significancia
corrplot(corr_mat, method = "color",
title = "Correlación entre variables numéricas",
tl.col = "black", tl.pos = "n",
mar = c(2, 1, 3, 1))
corr_mat
Age BMI WBC RBC
Age 1.000000e+00 -2.697598e-02 0.017346285 -0.003250116
BMI -2.697598e-02 1.000000e+00 0.037996220 -0.002756251
WBC 1.734628e-02 3.799622e-02 1.000000000 0.008365064
RBC -3.250116e-03 -2.756251e-03 0.008365064 1.000000000
HGB -1.346177e-02 5.997404e-02 0.007211737 0.042209841
Plat -1.613839e-03 -3.630193e-03 -0.013155218 0.034194997
AST.1 -2.071666e-02 -2.470297e-05 -0.006318532 0.014572461
ALT.1 6.781301e-03 3.583009e-02 -0.038879669 0.010662759
ALT.4 3.196612e-02 2.662224e-03 -0.014125104 -0.029854826
ALT.12 1.935010e-02 -6.091079e-02 -0.003728601 0.016937427
ALT.24 -4.395136e-05 5.571100e-03 -0.009768910 0.014521580
ALT.36 -6.659803e-03 -2.197531e-02 -0.045965023 0.048223756
ALT.48 2.816311e-02 1.068905e-03 -0.018168701 -0.058306939
ALT.after.24.w 7.176556e-03 -1.080194e-02 0.011200993 0.006522119
RNA.Base 2.077794e-02 -1.558458e-02 0.014803004 0.005794526
RNA.4 -1.133849e-02 3.555795e-02 0.022664875 0.018093935
RNA.12 -1.932151e-02 -2.149649e-02 -0.039336107 -0.067766722
RNA.EOT -5.130286e-02 -2.555149e-02 -0.019720903 -0.031623516
RNA.EF -3.682528e-02 -4.489250e-02 -0.042460781 -0.012911041
BH.grading -3.973584e-02 -2.393833e-02 0.029504155 -0.017467679
HGB Plat AST.1 ALT.1
Age -0.0134617685 -0.001613839 -2.071666e-02 0.006781301
BMI 0.0599740394 -0.003630193 -2.470297e-05 0.035830090
WBC 0.0072117366 -0.013155218 -6.318532e-03 -0.038879669
RBC 0.0422098411 0.034194997 1.457246e-02 0.010662759
HGB 1.0000000000 -0.007516561 -1.258791e-02 -0.014523142
Plat -0.0075165606 1.000000000 -4.447343e-03 0.046214537
AST.1 -0.0125879098 -0.004447343 1.000000e+00 0.037949039
ALT.1 -0.0145231419 0.046214537 3.794904e-02 1.000000000
ALT.4 0.0216958629 -0.025727845 8.137227e-03 -0.032283250
ALT.12 -0.0072591607 -0.041746382 -1.215106e-02 -0.044694783
ALT.24 0.0066981537 -0.004400589 -1.458897e-02 -0.041890540
ALT.36 -0.0396093534 0.002441219 -7.686043e-03 -0.016715133
ALT.48 -0.0327107416 -0.005981120 -9.058620e-03 0.029240228
ALT.after.24.w -0.0246369855 -0.035748502 2.120943e-03 -0.007038551
RNA.Base -0.0528185590 -0.039655767 -3.432854e-03 0.034882064
RNA.4 -0.0003533722 -0.039857847 -1.033735e-02 -0.013687496
RNA.12 0.0127061367 0.043738983 -1.145836e-02 0.009511748
RNA.EOT -0.0061691849 0.037606338 -4.288664e-02 -0.028658286
RNA.EF 0.0035481322 0.008469466 -8.738575e-03 -0.018706350
BH.grading 0.0207820734 0.033181397 -2.497076e-02 -0.012852154
ALT.4 ALT.12 ALT.24 ALT.36
Age 0.031966124 0.0193501045 -4.395136e-05 -0.0066598029
BMI 0.002662224 -0.0609107887 5.571100e-03 -0.0219753149
WBC -0.014125104 -0.0037286007 -9.768910e-03 -0.0459650229
RBC -0.029854826 0.0169374268 1.452158e-02 0.0482237564
HGB 0.021695863 -0.0072591607 6.698154e-03 -0.0396093534
Plat -0.025727845 -0.0417463821 -4.400589e-03 0.0024412187
AST.1 0.008137227 -0.0121510597 -1.458897e-02 -0.0076860430
ALT.1 -0.032283250 -0.0446947826 -4.189054e-02 -0.0167151327
ALT.4 1.000000000 0.0031361421 2.713221e-02 0.0141986244
ALT.12 0.003136142 1.0000000000 2.203490e-02 -0.0006370239
ALT.24 0.027132212 0.0220348963 1.000000e+00 -0.0078870641
ALT.36 0.014198624 -0.0006370239 -7.887064e-03 1.0000000000
ALT.48 -0.007019825 0.0131558494 -9.633634e-02 -0.0168930153
ALT.after.24.w 0.015592430 -0.0197839579 -2.639300e-02 -0.0300172598
RNA.Base -0.012105897 -0.0360096773 9.036060e-03 -0.0076068253
RNA.4 -0.009380897 -0.0163838506 -3.882051e-02 -0.0296143242
RNA.12 0.014877520 -0.0171655802 3.651826e-03 0.0143817313
RNA.EOT 0.048432454 -0.0279837611 -5.917538e-04 0.0260545124
RNA.EF 0.015079926 -0.0251411594 1.582293e-02 0.0181743137
BH.grading -0.026185381 -0.0038256167 -2.194802e-03 0.0089611399
ALT.48 ALT.after.24.w RNA.Base RNA.4
Age 0.028163106 0.007176556 0.020777939 -0.0113384878
BMI 0.001068905 -0.010801940 -0.015584578 0.0355579511
WBC -0.018168701 0.011200993 0.014803004 0.0226648747
RBC -0.058306939 0.006522119 0.005794526 0.0180939350
HGB -0.032710742 -0.024636986 -0.052818559 -0.0003533722
Plat -0.005981120 -0.035748502 -0.039655767 -0.0398578469
AST.1 -0.009058620 0.002120943 -0.003432854 -0.0103373517
ALT.1 0.029240228 -0.007038551 0.034882064 -0.0136874960
ALT.4 -0.007019825 0.015592430 -0.012105897 -0.0093808971
ALT.12 0.013155849 -0.019783958 -0.036009677 -0.0163838506
ALT.24 -0.096336341 -0.026392995 0.009036060 -0.0388205084
ALT.36 -0.016893015 -0.030017260 -0.007606825 -0.0296143242
ALT.48 1.000000000 0.006620724 0.019652518 -0.0040512609
ALT.after.24.w 0.006620724 1.000000000 0.027929973 0.0376994945
RNA.Base 0.019652518 0.027929973 1.000000000 0.0202476482
RNA.4 -0.004051261 0.037699495 0.020247648 1.0000000000
RNA.12 0.024724319 -0.016008194 -0.003811067 -0.0389631541
RNA.EOT -0.003858986 0.015741358 0.012455161 -0.0005597583
RNA.EF 0.007583896 0.008218462 0.011118219 -0.0537898540
BH.grading 0.039053295 0.022796550 -0.017975698 -0.0490383618
RNA.12 RNA.EOT RNA.EF BH.grading
Age -0.019321511 -0.0513028578 -0.0368252838 -0.0397358400
BMI -0.021496493 -0.0255514882 -0.0448924980 -0.0239383273
WBC -0.039336107 -0.0197209033 -0.0424607814 0.0295041546
RBC -0.067766722 -0.0316235165 -0.0129110410 -0.0174676790
HGB 0.012706137 -0.0061691849 0.0035481322 0.0207820734
Plat 0.043738983 0.0376063382 0.0084694658 0.0331813968
AST.1 -0.011458358 -0.0428866363 -0.0087385748 -0.0249707633
ALT.1 0.009511748 -0.0286582856 -0.0187063498 -0.0128521537
ALT.4 0.014877520 0.0484324543 0.0150799257 -0.0261853807
ALT.12 -0.017165580 -0.0279837611 -0.0251411594 -0.0038256167
ALT.24 0.003651826 -0.0005917538 0.0158229261 -0.0021948024
ALT.36 0.014381731 0.0260545124 0.0181743137 0.0089611399
ALT.48 0.024724319 -0.0038589856 0.0075838960 0.0390532950
ALT.after.24.w -0.016008194 0.0157413577 0.0082184620 0.0227965496
RNA.Base -0.003811067 0.0124551606 0.0111182188 -0.0179756978
RNA.4 -0.038963154 -0.0005597583 -0.0537898540 -0.0490383618
RNA.12 1.000000000 0.6046914218 0.6138921400 -0.0499342972
RNA.EOT 0.604691422 1.0000000000 0.6070418348 -0.0422752815
RNA.EF 0.613892140 0.6070418348 1.0000000000 0.0000676806
BH.grading -0.049934297 -0.0422752815 0.0000676806 1.0000000000
# Calcular el coeficiente de correlación de Spearman
cor.test(HCV$RNA.12, HCV$RNA.EOT, method = "spearman")
Spearman's rank correlation rho
data: HCV$RNA.12 and HCV$RNA.EOT
S = 173526496, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.6046914
cor.test(HCV$RNA.12, HCV$RNA.EF, method = "spearman")
Spearman's rank correlation rho
data: HCV$RNA.12 and HCV$RNA.EF
S = 169487705, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.6138921
cor.test(HCV$RNA.EOT, HCV$RNA.EF, method = "spearman")
Spearman's rank correlation rho
data: HCV$RNA.EOT and HCV$RNA.EF
S = 172494747, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.6070418
Como podemos observar varias correlaciones regulares y tres correlaciones buenas entre las variables, las correlaciones más altas no superan un factor de correlación de 0.61, sin embargo al realizar el test de correlación de Spearman se confirma que existe una correlación positiva y moderada entre las dos variables.
Variables con varianza cero o próxima a cero
En una distribución uniforme es muy poco probable que la varianza sea igual a cero ya que cada valor tiene la misma probabilidad de aparecer, y en esta base de datos tampoco se manejan datos muy pequeños por los que se pueda confundir una varianza cercana a cero, sin embargo realizaremos este paso para confirmarlo.
# Varianza de las variables numéricas
round(apply(mynum.norm, 2, var),2)
Age BMI WBC RBC HGB
0.09 0.10 0.09 0.08 0.12
Plat AST.1 ALT.1 ALT.4 ALT.12
0.08 0.09 0.08 0.09 0.09
ALT.24 ALT.36 ALT.48 ALT.after.24.w RNA.Base
0.09 0.05 0.04 0.03 0.09
RNA.4 RNA.12 RNA.EOT RNA.EF BH.grading
0.09 0.01 0.11 0.11 0.10
library(caret)
nearZeroVar(mynum.norm, saveMetrics = TRUE)
freqRatio percentUnique zeroVar nzv
Age 1.036364 2.1723389 FALSE FALSE
BMI 1.044643 1.0137581 FALSE FALSE
WBC 1.000000 94.2070963 FALSE FALSE
RBC 2.000000 99.9275887 FALSE FALSE
HGB 1.097872 0.4344678 FALSE FALSE
Plat 1.000000 99.2758870 FALSE FALSE
AST.1 1.181818 6.5170167 FALSE FALSE
ALT.1 1.200000 6.5170167 FALSE FALSE
ALT.4 1.038462 6.5170167 FALSE FALSE
ALT.12 1.000000 6.5170167 FALSE FALSE
ALT.24 1.080000 6.5170167 FALSE FALSE
ALT.36 1.041667 6.5170167 FALSE FALSE
ALT.48 1.041667 6.5170167 FALSE FALSE
ALT.after.24.w 1.043478 1.7378711 FALSE FALSE
RNA.Base 2.000000 99.9275887 FALSE FALSE
RNA.4 2.000000 99.9275887 FALSE FALSE
RNA.12 383.000000 72.3388849 FALSE FALSE
RNA.EOT 382.000000 72.4112962 FALSE FALSE
RNA.EF 380.000000 72.5561188 FALSE FALSE
BH.grading 1.150000 1.0137581 FALSE FALSE
Se comprueba que ninguna de las variables tiene una varianza igual a cero.
La selección de predictores es un paso necesario para identificar las variables más relevantes que contribuyen a la predicción del objetivo, en este caso de los estadios de FH. Después de haber realizado el análisis exploratorio de datos se ha filtrado con la técnica Ramdow Forest y una filtración Gini.
Importancia de las variables con Random Forest
El índice Gini en Random Forest es utilizado para medir la importancia de las variables en la predicción de la variable respuesta, por tanto nos será de ayuda al momento de mejorar el modelo.
Las variables con menos importancia son las variables cualitativas relacionadas con la sintomatología del paciente.
# Particion de los datos train/test
set.seed(77)
## Muestras que pertenecen al conjunto train
n_train <- createDataPartition(HCV$BH.staging, p = 0.7, list = FALSE)
## Eliminamos las variables con menos importancia
HCV2<- HCV3
HCV2 <- HCV2 %>%
select(-Epigastria.pain, -Gender, -Headache, -Nausea.Vomiting, -Jaundice, -Fatigue.Boneache, -Fever, -Diarrhea, -RNA.12, -RNA.EOT, -RNA.EF, -HGB, -BH.grading)
## Creamos los conjuntos train y test:
train.d <- HCV2[n_train,]
test.d <- HCV2[-n_train,]
## Variable objetivo por conjunto de datos
label_train <- HCV2[n_train,length(HCV2)]
label_test <- HCV2[-n_train,length(HCV2)]
Considerando que tanto predictores como variable respuesta tienen una
distribución uniforme los datos al ser escogidos al azar deberían
mantener la distribución, sin embargo para asegurarse de ello usamos la
función createDataPartition para mantener la proporción en
la partición de datos.
También hay que destacar que aunque los datos tienen una distribución uniforme han sido normalizados considerando que existen una gran variabilidad entre una variable y otra.
De los 1381 registros iniciales, el conjunto train contiene 968 registros y el conjunto test contiene 413 registros. Los porcentajes parecen indicar que los datos se han dividido equitativamente entre los subconjuntos de datos.
| F1 | F2 | F3 | F4 | |
|---|---|---|---|---|
| % Train | 0.24 | 0.24 | 0.26 | 0.26 |
| % Test | 0.24 | 0.24 | 0.26 | 0.26 |
# Preparamos los conjuntos de datos para que sean preprocesados
data_train <- train.d
data_test <- test.d
data_tn <- data_train
data_tt <- data_test
data_tn2 <- data_train
data_tt2 <- data_test
En el preprocesado de los datos, se han generado un total de 29 variables (28 predictores y la variable respuesta).
Utilizamos el paquete caret para generar y entrenar los
diferentes modelos de aprendizaje automático, proporcionando diferentes
hiperparámetros y buscando el modelo con mejor rendimiento.
Generamos el modelo KNN
# Cargar el paquete caret
library(caret)
particiones <- 20
repeticiones <- 20
hiperparámetros <- data.frame(k = c(5,10,15,20,25,30))
set.seed(12345)
seed <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seed[[i]] <- sample.int(1000, nrow(hiperparámetros))
}
seed[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# Entrenamiento
control_train <- trainControl(
method = "repeatedcv",
number = particiones,
repeats = repeticiones,
seed = seed,
returnResamp = "final",
verboseIter = FALSE,
allowParallel = TRUE
)
# Ajuste del modelo
set.seed(23456)
modelo_knn <- caret::train(
BH.staging ~ .,
data = data_tn,
method = "knn",
tuneGrid = hiperparámetros,
metric = "Accuracy",
trControl = control_train
)
modelo_knn
k-Nearest Neighbors
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (20 fold, repeated 20 times)
Summary of sample sizes: 920, 921, 920, 920, 920, 918, ...
Resampling results across tuning parameters:
k Accuracy Kappa
5 0.2511215 0.0003088570
10 0.2507081 -0.0006665558
15 0.2655902 0.0185926854
20 0.2631094 0.0152153544
25 0.2616867 0.0133653206
30 0.2574146 0.0071132299
Accuracy was used to select the optimal model using the largest value.
The final value used for the model was k = 15.
# Gráfico
ggplot(modelo_knn, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo KNN") +
theme_bw()
# Obtener la matriz de confusión
predicciones_knn <- predict(modelo_knn, newdata = data_tt, type = "raw")
conf_mat_knn <- caret::confusionMatrix(
factor(predicciones_knn, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
# Crear objeto stats_class_knn con las estadísticas extraídas
stats_class_knn <- data.frame(
model = "KNN",
precision = conf_mat_knn$overall["Accuracy"],
FN = conf_mat_knn$table[2,1],
FP = conf_mat_knn$table[1,2],
error.rate = 1 - conf_mat_knn$overall["Accuracy"],
kappa = conf_mat_knn$overall["Kappa"],
sensibilidad = mean(conf_mat_knn$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_knn$byClass[,"Specificity"]),
precisión = mean(conf_mat_knn$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_knn$byClass[,"Recall"]),
f.medida = mean(conf_mat_knn$byClass[,"F1"])
)
stats_class_knn
model precision FN FP error.rate kappa sensibilidad especificidad
Accuracy KNN 0.2615012 24 15 0.7384988 0.01361743 0.2606731 0.7533485
precisión recuperación f.medida
Accuracy 0.2607384 0.2606731 0.2583652
Generamos el modelo NB.
particiones <- 10
repeticiones <- 10
# Definir los hiperparámetros para Naive Bayes
hiperparámetros <- expand.grid(
laplace = c(0, 1, 2, 3),
usekernel = c(FALSE, TRUE),
adjust = c(FALSE, TRUE)
)
set.seed(12345)
seed <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seed[[i]] <- sample.int(1000, nrow(hiperparámetros))
}
seed[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# Entrenamiento
control_train <- trainControl(
method = "repeatedcv",
number = particiones,
repeats = repeticiones,
seed = seed,
returnResamp = "final",
verboseIter = FALSE,
allowParallel = TRUE
)
# Ajuste del modelo Naive Bayes
set.seed(23456)
modelo_nb <- caret::train(
BH.staging ~ .,
data = data_tn,
method = "naive_bayes",
tuneGrid = hiperparámetros,
metric = "Accuracy",
trControl = control_train
)
modelo_nb
Naive Bayes
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 872, 872, 872, 871, 871, 871, ...
Resampling results across tuning parameters:
laplace usekernel adjust Accuracy Kappa
0 FALSE FALSE 0.2295835 -0.02930784
0 FALSE TRUE 0.2295835 -0.02930784
0 TRUE FALSE NaN NaN
0 TRUE TRUE 0.2231781 -0.03834394
1 FALSE FALSE 0.2295835 -0.02930784
1 FALSE TRUE 0.2295835 -0.02930784
1 TRUE FALSE NaN NaN
1 TRUE TRUE 0.2231781 -0.03834394
2 FALSE FALSE 0.2295835 -0.02930784
2 FALSE TRUE 0.2295835 -0.02930784
2 TRUE FALSE NaN NaN
2 TRUE TRUE 0.2231781 -0.03834394
3 FALSE FALSE 0.2295835 -0.02930784
3 FALSE TRUE 0.2295835 -0.02930784
3 TRUE FALSE NaN NaN
3 TRUE TRUE 0.2231781 -0.03834394
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were laplace = 0, usekernel = FALSE
and adjust = FALSE.
# Gráfico
ggplot(modelo_nb, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo NB") +
theme_bw()
# Obtener la matriz de confusión
predicciones_nb <- predict(modelo_nb, newdata = data_tt, type = "raw")
conf_mat_nb <- caret::confusionMatrix(
factor(predicciones_nb, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
# Crear objeto stats_class_nb con las estadísticas extraídas
stats_class_nb <- data.frame(
model = "Naive Bayes",
precision = conf_mat_nb$overall["Accuracy"],
FN = conf_mat_nb$table[2,1],
FP = conf_mat_nb$table[1,2],
error.rate = 1 - conf_mat_nb$overall["Accuracy"],
kappa = conf_mat_nb$overall["Kappa"],
sensibilidad = mean(conf_mat_nb$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_nb$byClass[,"Specificity"]),
precisión = mean(conf_mat_nb$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_nb$byClass[,"Recall"]),
f.medida = mean(conf_mat_nb$byClass[,"F1"])
)
stats_class_nb
model precision FN FP error.rate kappa sensibilidad
Accuracy Naive Bayes 0.2445521 30 12 0.7554479 -0.009281669 0.2425912
especificidad precisión recuperación f.medida
Accuracy 0.7477358 0.2313054 0.2425912 0.2278643
Generamos el modelo MLP.
# Número de particiones y repeticiones
particiones <- 20
repeticiones <- 20
#hiperparametros <- expand.grid(size = c(1:20),
# decay = c(0.0001, 0.1, 0.5))
hiperparametros <- expand.grid(size = c(1:5),
decay = c(0.0001))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_mlp <- caret::train(BH.staging ~ .,
data = data_tn,
method = "mlpWeightDecay",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train,
learnFunc = "Std_Backpropagation")
modelo_mlp
Multi-Layer Perceptron
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (20 fold, repeated 20 times)
Summary of sample sizes: 921, 920, 918, 920, 919, 920, ...
Resampling results across tuning parameters:
size Accuracy Kappa
1 0.2661983 0.01758281
2 0.2698890 0.02238041
3 0.2690820 0.02039518
4 0.2659637 0.01840606
5 0.2662596 0.01786372
Tuning parameter 'decay' was held constant at a value of 1e-04
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were size = 2 and decay = 1e-04.
# REPRESENTACIÓN GRÁFICA
ggplot(modelo_mlp, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo MLP") +
theme_bw()
# Predicciones
predicciones_mlp <- predict(modelo_mlp, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_mlp <- caret::confusionMatrix(factor(predicciones_mlp, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_mlp
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 0 0 0 0
F2 1 0 1 1
F3 0 0 0 0
F4 99 99 105 107
Overall Statistics
Accuracy : 0.2591
95% CI : (0.2175, 0.3042)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.5633
Kappa : -0.0031
Mcnemar's Test P-Value : NA
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.0000 0.000000 0.0000 0.990741
Specificity 1.0000 0.990446 1.0000 0.006557
Pos Pred Value NaN 0.000000 NaN 0.260976
Neg Pred Value 0.7579 0.758537 0.7433 0.666667
Prevalence 0.2421 0.239709 0.2567 0.261501
Detection Rate 0.0000 0.000000 0.0000 0.259080
Detection Prevalence 0.0000 0.007264 0.0000 0.992736
Balanced Accuracy 0.5000 0.495223 0.5000 0.498649
stats_class_mlp <- data.frame(model = "MLP",
precision = conf_mat_mlp$overall["Accuracy"],
FN = conf_mat_mlp$table[2,1],
FP = conf_mat_mlp$table[1,2],
error.rate = 1 - conf_mat_mlp$overall["Accuracy"],
kappa = conf_mat_mlp$overall["Kappa"],
sensibilidad = mean(conf_mat_mlp$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_mlp$byClass[,"Specificity"]),
precisión = mean(conf_mat_mlp$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_mlp$byClass[,"Recall"]),
f.medida = mean(conf_mat_mlp$byClass[,"F1"])
)
stats_class_mlp
model precision FN FP error.rate kappa sensibilidad
Accuracy MLP 0.2590799 1 0 0.7409201 -0.003063687 0.2476852
especificidad precisión recuperación f.medida
Accuracy 0.7492508 NaN 0.2476852 NA
Generamos el modelo SVM-lineal.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- data.frame(C = c(40,50,60,70,80,90))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_svmlineal <- caret::train(BH.staging ~ ., data = data_tn,
method = "svmLinear",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train)
modelo_svmlineal
Support Vector Machines with Linear Kernel
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
C Accuracy Kappa
40 0.2374332 -0.01855302
50 0.2369156 -0.01923795
60 0.2372270 -0.01882160
70 0.2372270 -0.01882700
80 0.2371228 -0.01897575
90 0.2366073 -0.01966175
Accuracy was used to select the optimal model using the largest value.
The final value used for the model was C = 40.
# Predicciones
predicciones_svmlineal <- predict(modelo_svmlineal, newdata = data_tt, type = "raw")
conf_mat_svmlineal <- caret::confusionMatrix(factor(predicciones_svmlineal, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_svmlineal
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 12 10 13 15
F2 32 26 32 28
F3 16 24 17 16
F4 40 39 44 49
Overall Statistics
Accuracy : 0.2518
95% CI : (0.2107, 0.2966)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.6905
Kappa : -3e-04
Mcnemar's Test P-Value : 6.501e-07
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.12000 0.26263 0.16038 0.4537
Specificity 0.87859 0.70701 0.81759 0.5967
Pos Pred Value 0.24000 0.22034 0.23288 0.2849
Neg Pred Value 0.75758 0.75254 0.73824 0.7552
Prevalence 0.24213 0.23971 0.25666 0.2615
Detection Rate 0.02906 0.06295 0.04116 0.1186
Detection Prevalence 0.12107 0.28571 0.17676 0.4165
Balanced Accuracy 0.49930 0.48482 0.48898 0.5252
# REPRESENTACIÓN GRÁFICA
ggplot(modelo_svmlineal, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo SVMlineal") +
theme_bw()
stats_class_svmlineal <- data.frame(model = "SVMlineal",
precision = conf_mat_svmlineal$overall["Accuracy"],
FN = conf_mat_svmlineal$table[2,1],
FP = conf_mat_svmlineal$table[1,2],
error.rate = 1 - conf_mat_svmlineal$overall["Accuracy"],
kappa = conf_mat_svmlineal$overall["Kappa"],
sensibilidad = mean(conf_mat_svmlineal$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_svmlineal$byClass[,"Specificity"]),
precisión = mean(conf_mat_svmlineal$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_svmlineal$byClass[,"Recall"]),
f.medida = mean(conf_mat_svmlineal$byClass[,"F1"])
)
stats_class_svmlineal
model precision FN FP error.rate kappa sensibilidad
Accuracy SVMlineal 0.251816 32 10 0.748184 -0.0003449006 0.2491768
especificidad precisión recuperación f.medida
Accuracy 0.7499779 0.2445249 0.2491768 0.2348939
Generamos el modelo SVM-polynomial.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- expand.grid(degree = c(2),
scale = c(0.1,0.2,0.3,0.5),
C = c(10,20,30,40))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_svmPoly <- caret::train(BH.staging ~ ., data = data_tn,
method = "svmPoly",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train)
modelo_svmPoly
Support Vector Machines with Polynomial Kernel
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
scale C Accuracy Kappa
0.1 10 0.2349117 -0.01967680
0.1 20 0.2346131 -0.01997535
0.1 30 0.2343134 -0.02036599
0.1 40 0.2345132 -0.02000844
0.2 10 0.2342039 -0.02043187
0.2 20 0.2368814 -0.01681812
0.2 30 0.2382163 -0.01506727
0.2 40 0.2365752 -0.01725708
0.3 10 0.2378125 -0.01559064
0.3 20 0.2372948 -0.01628814
0.3 30 0.2362659 -0.01762581
0.3 40 0.2373915 -0.01614189
0.5 10 0.2367814 -0.01694943
0.5 20 0.2374968 -0.01600440
0.5 30 0.2377040 -0.01571126
0.5 40 0.2379113 -0.01543251
Tuning parameter 'degree' was held constant at a value of 2
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were degree = 2, scale = 0.2 and C = 30.
# Predicciones
predicciones_svmPoly <- predict(modelo_svmPoly, newdata = data_tt,
type = "raw")
predicciones_svmPoly
[1] F3 F2 F1 F1 F3 F4 F3 F3 F1 F4 F1 F2 F3 F2 F4 F1 F3 F1 F2 F4 F4 F3 F2 F2 F3
[26] F1 F3 F2 F3 F2 F1 F2 F3 F1 F2 F1 F2 F1 F1 F2 F1 F2 F3 F1 F4 F1 F2 F1 F3 F4
[51] F2 F1 F2 F4 F2 F2 F4 F2 F2 F3 F3 F1 F4 F3 F2 F1 F4 F3 F2 F3 F2 F1 F2 F4 F4
[76] F1 F1 F2 F3 F1 F4 F4 F2 F1 F2 F3 F1 F3 F1 F4 F4 F2 F1 F2 F3 F2 F4 F4 F1 F3
[101] F2 F2 F4 F4 F1 F3 F4 F2 F3 F1 F3 F2 F2 F3 F2 F4 F2 F2 F4 F4 F2 F4 F1 F4 F1
[126] F2 F4 F4 F4 F4 F4 F1 F1 F1 F4 F2 F2 F3 F2 F1 F3 F2 F4 F2 F3 F1 F2 F4 F4 F2
[151] F4 F4 F3 F4 F2 F2 F1 F3 F3 F4 F3 F4 F1 F2 F2 F1 F1 F3 F4 F1 F2 F1 F2 F2 F1
[176] F3 F2 F3 F4 F3 F3 F4 F1 F3 F3 F1 F4 F2 F2 F2 F2 F1 F4 F2 F3 F2 F2 F3 F3 F4
[201] F4 F2 F4 F3 F4 F3 F4 F1 F2 F3 F4 F1 F2 F4 F1 F1 F2 F4 F2 F3 F3 F3 F2 F4 F2
[226] F4 F1 F2 F3 F2 F4 F3 F1 F3 F2 F4 F1 F1 F4 F1 F1 F2 F3 F1 F1 F2 F1 F3 F4 F3
[251] F4 F2 F4 F1 F3 F4 F1 F4 F1 F3 F3 F2 F2 F2 F1 F3 F2 F2 F1 F2 F4 F2 F3 F4 F1
[276] F4 F2 F2 F2 F1 F2 F3 F1 F4 F1 F2 F4 F1 F2 F4 F4 F3 F4 F4 F4 F3 F1 F2 F4 F4
[301] F3 F1 F3 F4 F1 F1 F1 F3 F2 F2 F4 F2 F1 F4 F3 F2 F3 F2 F4 F3 F4 F2 F1 F3 F1
[326] F4 F2 F1 F2 F4 F4 F3 F3 F2 F2 F2 F4 F4 F4 F2 F3 F2 F1 F4 F4 F4 F1 F4 F2 F2
[351] F2 F1 F4 F4 F2 F4 F1 F2 F3 F1 F2 F3 F4 F4 F4 F1 F1 F3 F2 F1 F3 F4 F2 F1 F4
[376] F3 F1 F1 F2 F1 F3 F2 F1 F4 F2 F3 F4 F2 F1 F1 F3 F1 F2 F2 F2 F4 F4 F3 F1 F3
[401] F3 F3 F3 F4 F2 F1 F2 F3 F2 F1 F2 F4 F1
Levels: F1 F2 F3 F4
# Evaluación
conf_mat_svmPoly <- caret::confusionMatrix(factor(predicciones_svmPoly, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_svmPoly
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 22 21 30 26
F2 25 32 39 25
F3 31 14 14 29
F4 22 32 23 28
Overall Statistics
Accuracy : 0.2324
95% CI : (0.1925, 0.2762)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.92057
Kappa : -0.0226
Mcnemar's Test P-Value : 0.02917
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.22000 0.32323 0.1321 0.2593
Specificity 0.75399 0.71656 0.7590 0.7475
Pos Pred Value 0.22222 0.26446 0.1591 0.2667
Neg Pred Value 0.75159 0.77055 0.7169 0.7403
Prevalence 0.24213 0.23971 0.2567 0.2615
Detection Rate 0.05327 0.07748 0.0339 0.0678
Detection Prevalence 0.23971 0.29298 0.2131 0.2542
Balanced Accuracy 0.48700 0.51990 0.4455 0.5034
# REPRESENTACIÓN GRÁFICA
ggplot(modelo_svmPoly, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo SVMpoly") +
theme_bw()
stats_class_svmPoly <- data.frame(model = "SVMpoly",
precision = conf_mat_svmPoly$overall["Accuracy"],
FN = conf_mat_svmPoly$table[2,1],
FP = conf_mat_svmPoly$table[1,2],
error.rate = 1 - conf_mat_svmPoly$overall["Accuracy"],
kappa = conf_mat_svmPoly$overall["Kappa"],
sensibilidad = mean(conf_mat_svmPoly$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_svmPoly$byClass[,"Specificity"]),
precisión = mean(conf_mat_svmPoly$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_svmPoly$byClass[,"Recall"]),
f.medida = mean(conf_mat_svmPoly$byClass[,"F1"])
)
stats_class_svmPoly
model precision FN FP error.rate kappa sensibilidad
Accuracy SVMpoly 0.2324455 25 21 0.7675545 -0.02264455 0.2336418
especificidad precisión recuperación f.medida
Accuracy 0.7442632 0.2281107 0.2336418 0.2298138
Generamos el modelo SVM-radial.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- expand.grid(sigma = c(0.1, 0.5, 3,5,10),
C = c(10,15,20,40,50))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_svmRadial <- caret::train(BH.staging ~ ., data = data_tn,
method = "svmRadial",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train)
modelo_svmRadial
Support Vector Machines with Radial Basis Function Kernel
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
sigma C Accuracy Kappa
0.1 10 0.2482211 -0.002431678
0.1 15 0.2484274 -0.002163353
0.1 20 0.2484274 -0.002163353
0.1 40 0.2484274 -0.002163353
0.1 50 0.2484274 -0.002163353
0.5 10 0.2674095 0.013904974
0.5 15 0.2674095 0.013904974
0.5 20 0.2674095 0.013904974
0.5 40 0.2674095 0.013904974
0.5 50 0.2674095 0.013904974
3.0 10 0.2603350 0.000000000
3.0 15 0.2603350 0.000000000
3.0 20 0.2603350 0.000000000
3.0 40 0.2603350 0.000000000
3.0 50 0.2603350 0.000000000
5.0 10 0.2603350 0.000000000
5.0 15 0.2603350 0.000000000
5.0 20 0.2603350 0.000000000
5.0 40 0.2603350 0.000000000
5.0 50 0.2603350 0.000000000
10.0 10 0.2603350 0.000000000
10.0 15 0.2603350 0.000000000
10.0 20 0.2603350 0.000000000
10.0 40 0.2603350 0.000000000
10.0 50 0.2603350 0.000000000
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were sigma = 0.5 and C = 10.
# Predicciones
predicciones_svmRadial <- predict(modelo_svmRadial, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_svmRadial <- caret::confusionMatrix(factor(predicciones_svmRadial, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_svmRadial
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 7 7 6 3
F2 3 3 11 10
F3 36 28 40 35
F4 54 61 49 60
Overall Statistics
Accuracy : 0.2663
95% CI : (0.2243, 0.3118)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.4299
Kappa : 0.0121
Mcnemar's Test P-Value : <2e-16
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.07000 0.030303 0.37736 0.5556
Specificity 0.94888 0.923567 0.67752 0.4623
Pos Pred Value 0.30435 0.111111 0.28777 0.2679
Neg Pred Value 0.76154 0.751295 0.75912 0.7460
Prevalence 0.24213 0.239709 0.25666 0.2615
Detection Rate 0.01695 0.007264 0.09685 0.1453
Detection Prevalence 0.05569 0.065375 0.33656 0.5424
Balanced Accuracy 0.50944 0.476935 0.52744 0.5089
# REPRESENTACIÓN GRÁFICA
ggplot(modelo_svmRadial, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo SVMradial") +
theme_bw()
stats_class_svmRadial <- data.frame(model = "SVMradial",
precision = conf_mat_svmRadial$overall["Accuracy"],
FN = conf_mat_svmRadial$table[2,1],
FP = conf_mat_svmRadial$table[1,2],
error.rate = 1 - conf_mat_svmRadial$overall["Accuracy"],
kappa = conf_mat_svmRadial$overall["Kappa"],
sensibilidad = mean(conf_mat_svmRadial$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_svmRadial$byClass[,"Specificity"]),
precisión = mean(conf_mat_svmRadial$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_svmRadial$byClass[,"Recall"]),
f.medida = mean(conf_mat_svmRadial$byClass[,"F1"])
)
stats_class_svmRadial
model precision FN FP error.rate kappa sensibilidad
Accuracy SVMradial 0.2663438 3 7 0.7336562 0.01208652 0.2583043
especificidad precisión recuperación f.medida
Accuracy 0.753067 0.2427715 0.2583043 0.2123541
Generamos el modelo C5.0.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- data.frame(parameter = "none")
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_C5.0Tree <- caret::train(BH.staging ~ ., data = data_tn,
method = "C5.0Tree",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train)
modelo_C5.0Tree
Single C5.0 Tree
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results:
Accuracy Kappa
0.2475711 -0.00405449
summary(modelo_C5.0Tree$finalModel)
Call:
C50:::C5.0.default(x = x, y = y, weights = wts)
C5.0 [Release 2.07 GPL Edition] Mon Apr 24 12:24:29 2023
-------------------------------
Class specified by attribute `outcome'
Read 968 cases (16 attributes) from undefined.data
Decision tree:
BMI <= 0.4615385:
:...AST.1 > 0.7640449:
: :...ALT.1 <= 0.05617978:
: : :...RBC <= 0.6272686: F3 (6)
: : : RBC > 0.6272686: F1 (4)
: : ALT.1 > 0.05617978:
: : :...ALT.48 <= 0.08988764:
: : :...RNA.4 <= 0.4694727:
: : : :...ALT.4 <= 0.5168539: F4 (4/1)
: : : : ALT.4 > 0.5168539: F3 (2)
: : : RNA.4 > 0.4694727:
: : : :...RBC <= 0.7754056: F2 (4/1)
: : : RBC > 0.7754056: F4 (4)
: : ALT.48 > 0.08988764:
: : :...RNA.4 > 0.8480108:
: : :...ALT.24 <= 0.6179775: F4 (2)
: : : ALT.24 > 0.6179775:
: : : :...WBC <= 0.6020856: F1 (6/1)
: : : WBC > 0.6020856: F3 (2)
: : RNA.4 <= 0.8480108:
: : :...Age > 0.4827586:
: : :...RBC > 0.8265383: F3 (3/1)
: : : RBC <= 0.8265383:
: : : :...ALT.12 <= 0.3033708: F3 (9/1)
: : : ALT.12 > 0.3033708:
: : : :...Plat > 0.6226405: F2 (13)
: : : Plat <= 0.6226405:
: : : :...ALT.1 > 0.6179775: F3 (5)
: : : ALT.1 <= 0.6179775:
: : : :...ALT.1 <= 0.4269663: F3 (2)
: : : ALT.1 > 0.4269663: F2 (4)
: : Age <= 0.4827586:
: : :...ALT.36 > 0.7865168:
: : :...BMI <= 0.1538462: F4 (4/1)
: : : BMI > 0.1538462: F3 (3)
: : ALT.36 <= 0.7865168:
: : :...ALT.after.24.w > 0.7826087: F2 (4)
: : ALT.after.24.w <= 0.7826087:
: : :...Age > 0.3448276:
: : :...RNA.Base <= 0.6924855: F1 (5/1)
: : : RNA.Base > 0.6924855: F4 (4/1)
: : Age <= 0.3448276:
: : :...ALT.1 > 0.752809: F1 (3/1)
: : ALT.1 <= 0.752809:
: : :...RNA.4 <= 0.373249: F1 (3/1)
: : RNA.4 > 0.373249:
: : :...ALT.24 <= 0.7191011: F2 (8/1)
: : ALT.24 > 0.7191011: F3 (2)
: AST.1 <= 0.7640449:
: :...ALT.12 <= 0.04494382:
: :...ALT.after.24.w <= 0.08695652: F2 (3/1)
: : ALT.after.24.w > 0.08695652:
: : :...RBC <= 0.4163593: F1 (3/1)
: : RBC > 0.4163593:
: : :...ALT.4 <= 0.2134831: F1 (3/1)
: : ALT.4 > 0.2134831: F3 (8)
: ALT.12 > 0.04494382:
: :...ALT.after.24.w <= 0.4782609:
: :...Age <= 0.06896552:
: : :...Plat > 0.6581442: F1 (4)
: : : Plat <= 0.6581442:
: : : :...Plat > 0.4399442: F4 (4)
: : : Plat <= 0.4399442:
: : : :...Age > 0.03448276: F4 (2)
: : : Age <= 0.03448276:
: : : :...ALT.1 <= 0.6853933: F1 (7/1)
: : : ALT.1 > 0.6853933: F4 (3/1)
: : Age > 0.06896552:
: : :...ALT.36 <= 0.08988764:
: : :...RNA.Base <= 0.3228641: F2 (4)
: : : RNA.Base > 0.3228641: F4 (4/1)
: : ALT.36 > 0.08988764:
: : :...Plat <= 0.05252864:
: : :...ALT.1 <= 0.1460674: F3 (3)
: : : ALT.1 > 0.1460674: F2 (3)
: : Plat > 0.05252864:
: : :...ALT.1 > 0.752809:
: : :...RNA.4 > 0.7888218:
: : : :...Age <= 0.4137931: F2 (5)
: : : : Age > 0.4137931: F1 (3/1)
: : : RNA.4 <= 0.7888218:
: : : :...RBC <= 0.3398761: F3 (5/1)
: : : RBC > 0.3398761:
: : : :...ALT.24 <= 0.1011236: F3 (2)
: : : ALT.24 > 0.1011236:
: : : :...ALT.4 <= 0.1573034: F2 (2)
: : : ALT.4 > 0.1573034:
: : : :...ALT.48 <= 0.6516854: F1 (14/1)
: : : ALT.48 > 0.6516854:
: : : :...WBC > 0.4070252: F4 (4)
: : : WBC <= 0.4070252:
: : : :...Age <= 0.6896552: F2 (2)
: : : Age > 0.6896552: F1 (2)
: : ALT.1 <= 0.752809:
: : :...ALT.4 > 0.9325843: F2 (5/1)
: : ALT.4 <= 0.9325843:
: : :...Plat > 0.812478:
: : :...RNA.4 <= 0.2695684:
: : : :...WBC <= 0.3960483: F4 (2)
: : : : WBC > 0.3960483: F3 (3)
: : : RNA.4 > 0.2695684:
: : : :...ALT.4 <= 0.7191011:
: : : :...WBC <= 0.2881449: F3 (2)
: : : : WBC > 0.2881449: F1 (9/1)
: : : ALT.4 > 0.7191011:
: : : :...WBC <= 0.5615807: F1 (2)
: : : WBC > 0.5615807: F4 (2)
: : Plat <= 0.812478:
: : :...ALT.12 <= 0.4831461:
: : :...RNA.4 <= 0.1410989: F4 (5)
: : : RNA.4 > 0.1410989:
: : : :...Plat <= 0.1263235: F1 (3/1)
: : : Plat > 0.1263235:
: : : :...WBC > 0.5037321:
: : : :...ALT.12 <= 0.2134831: F4 (2)
: : : : ALT.12 > 0.2134831: [S1]
: : : WBC <= 0.5037321:
: : : :...ALT.48 > 0.8089887: F2 (3)
: : : ALT.48 <= 0.8089887:
: : : :...ALT.1 <= 0.3033708: [S2]
: : : ALT.1 > 0.3033708: [S3]
: : ALT.12 > 0.4831461:
: : :...Plat > 0.6268818:
: : :...RNA.4 <= 0.1373751: F2 (2)
: : : RNA.4 > 0.1373751: F4 (14/2)
: : Plat <= 0.6268818:
: : :...ALT.12 > 0.7865168:
: : :...RBC <= 0.8629725: F1 (7)
: : : RBC > 0.8629725: F3 (2)
: : ALT.12 <= 0.7865168:
: : :...ALT.24 > 0.8426966:
: : :...ALT.12 <= 0.5842696: F1 (3)
: : : ALT.12 > 0.5842696: F4 (2)
: : ALT.24 <= 0.8426966:
: : :...RNA.Base <= 0.1421885: F3 (3)
: : RNA.Base > 0.1421885: [S4]
: ALT.after.24.w > 0.4782609:
: :...ALT.12 > 0.7640449:
: :...ALT.after.24.w > 0.9565217:
: : :...ALT.36 <= 0.4269663: F3 (3)
: : : ALT.36 > 0.4269663:
: : : :...Age <= 0.1724138: F3 (2)
: : : Age > 0.1724138: F4 (2)
: : ALT.after.24.w <= 0.9565217:
: : :...WBC > 0.8446762:
: : :...ALT.24 <= 0.3820225: F1 (2)
: : : ALT.24 > 0.3820225: F3 (4)
: : WBC <= 0.8446762:
: : :...Plat > 0.8774456: F1 (4)
: : Plat <= 0.8774456:
: : :...ALT.4 <= 0.3820225:
: : :...WBC <= 0.8316136: F1 (8/1)
: : : WBC > 0.8316136: F4 (2)
: : ALT.4 > 0.3820225:
: : :...RBC <= 0.1343212: F3 (3/1)
: : RBC > 0.1343212: F4 (12/1)
: ALT.12 <= 0.7640449:
: :...RBC > 0.8252838:
: :...Plat <= 0.5872193:
: : :...ALT.after.24.w <= 0.8695652: F3 (8/1)
: : : ALT.after.24.w > 0.8695652: F1 (4/1)
: : Plat > 0.5872193:
: : :...ALT.24 > 0.2808989: F2 (10/2)
: : ALT.24 <= 0.2808989:
: : :...RBC <= 0.8555975: F3 (2)
: : RBC > 0.8555975: F4 (2)
: RBC <= 0.8252838:
: :...AST.1 <= 0.07865169:
: :...ALT.4 <= 0.8764045: F4 (13/2)
: : ALT.4 > 0.8764045: F1 (2)
: AST.1 > 0.07865169:
: :...ALT.24 > 0.6629214:
: :...ALT.36 > 0.5168539: F4 (14/4)
: : ALT.36 <= 0.5168539:
: : :...ALT.after.24.w <= 0.8260869:
: : :...AST.1 <= 0.3370787: F3 (3)
: : : AST.1 > 0.3370787: F1 (5/1)
: : ALT.after.24.w > 0.8260869:
: : :...RNA.Base <= 0.2988623: F1 (2/1)
: : RNA.Base > 0.2988623: F4 (6/1)
: ALT.24 <= 0.6629214:
: :...ALT.12 <= 0.4269663:
: :...ALT.1 <= 0.4157303:
: : :...RBC > 0.3016891: F3 (7/1)
: : : RBC <= 0.3016891:
: : : :...WBC <= 0.5536773: F1 (3)
: : : WBC > 0.5536773: F2 (2)
: : ALT.1 > 0.4157303:
: : :...Age <= 0.5517241: F1 (9/2)
: : Age > 0.5517241:
: : :...ALT.1 <= 0.8539326: F4 (6/1)
: : ALT.1 > 0.8539326: F3 (2)
: ALT.12 > 0.4269663:
: :...ALT.48 <= 0.4494382:
: :...ALT.4 > 0.9101124: F3 (2)
: : ALT.4 <= 0.9101124:
: : :...ALT.after.24.w <= 0.9130435: F4 (11/2)
: : ALT.after.24.w > 0.9130435: F2 (2)
: ALT.48 > 0.4494382:
: :...ALT.36 <= 0.02247191: F4 (2)
: ALT.36 > 0.02247191:
: :...ALT.24 > 0.505618:
: :...Age <= 0.3448276: F4 (2)
: : Age > 0.3448276: F2 (2)
: ALT.24 <= 0.505618:
: :...ALT.after.24.w > 0.8260869:
: :...ALT.12 <= 0.5505618: F2 (3)
: : ALT.12 > 0.5505618: F1 (3/1)
: ALT.after.24.w <= 0.8260869:
: :...ALT.36 > 0.6629214: F3 (4)
: ALT.36 <= 0.6629214: [S5]
BMI > 0.4615385:
:...Plat > 0.971068:
:...Age <= 0.5862069: F2 (7/1)
: Age > 0.5862069:
: :...ALT.12 <= 0.6292135: F3 (4/1)
: ALT.12 > 0.6292135: F2 (2)
Plat <= 0.971068:
:...Age > 0.5517241:
:...RNA.4 <= 0.4070092:
: :...BMI <= 0.5384616:
: : :...RNA.4 <= 0.04654451: F1 (2)
: : : RNA.4 > 0.04654451:
: : : :...RNA.4 > 0.2394163: F4 (2)
: : : RNA.4 <= 0.2394163:
: : : :...Age <= 0.6896552: F2 (3/1)
: : : Age > 0.6896552: F3 (4)
: : BMI > 0.5384616:
: : :...ALT.48 > 0.741573:
: : :...Age <= 0.7586207:
: : : :...ALT.1 <= 0.8089887: F4 (6)
: : : : ALT.1 > 0.8089887: F1 (2)
: : : Age > 0.7586207:
: : : :...RBC <= 0.2869931: F1 (3/1)
: : : RBC > 0.2869931: F2 (5/1)
: : ALT.48 <= 0.741573:
: : :...Age > 0.7931035:
: : :...ALT.after.24.w <= 0.04347826: F1 (2)
: : : ALT.after.24.w > 0.04347826:
: : : :...AST.1 <= 0.5168539: F2 (10)
: : : AST.1 > 0.5168539:
: : : :...ALT.24 <= 0.2696629: F3 (3/1)
: : : ALT.24 > 0.2696629: F2 (7/2)
: : Age <= 0.7931035:
: : :...ALT.24 > 0.9101124: F1 (4/1)
: : ALT.24 <= 0.9101124:
: : :...ALT.36 > 0.3707865:
: : :...RNA.4 <= 0.3351882: F2 (14/1)
: : : RNA.4 > 0.3351882: F1 (3/1)
: : ALT.36 <= 0.3707865:
: : :...BMI > 0.9230769: F1 (2/1)
: : BMI <= 0.9230769:
: : :...Plat <= 0.394347: F4 (3)
: : Plat > 0.394347: F1 (5/1)
: RNA.4 > 0.4070092:
: :...Plat > 0.8752651:
: :...BMI <= 0.6923077: F1 (2/1)
: : BMI > 0.6923077: F2 (6)
: Plat <= 0.8752651:
: :...BMI > 0.7692308:
: :...ALT.1 <= 0.3932584:
: : :...BMI <= 0.8461539:
: : : :...ALT.24 <= 0.5280899: F1 (3/1)
: : : : ALT.24 > 0.5280899: F2 (5)
: : : BMI > 0.8461539:
: : : :...ALT.after.24.w <= 0.6521739:
: : : :...ALT.4 <= 0.7191011: F3 (8/1)
: : : : ALT.4 > 0.7191011: F1 (4)
: : : ALT.after.24.w > 0.6521739:
: : : :...ALT.1 <= 0.3033708: F2 (5/1)
: : : ALT.1 > 0.3033708: F1 (2)
: : ALT.1 > 0.3932584:
: : :...ALT.1 <= 0.7752809:
: : :...WBC <= 0.2667398: F2 (3/1)
: : : WBC > 0.2667398: F4 (7/1)
: : ALT.1 > 0.7752809:
: : :...Plat <= 0.3123768: F2 (2)
: : Plat > 0.3123768:
: : :...ALT.4 > 0.1235955: F3 (6)
: : ALT.4 <= 0.1235955:
: : :...Plat <= 0.6354542: F4 (3)
: : Plat > 0.6354542: F1 (2/1)
: BMI <= 0.7692308:
: :...RBC > 0.917794:
: :...ALT.12 <= 0.4831461: F2 (3)
: : ALT.12 > 0.4831461: F1 (2/1)
: RBC <= 0.917794:
: :...Age <= 0.5862069:
: :...ALT.12 > 0.5955056: F3 (2)
: : ALT.12 <= 0.5955056:
: : :...ALT.4 <= 0.752809: F1 (2/1)
: : ALT.4 > 0.752809: F2 (2)
: Age > 0.5862069:
: :...RNA.Base > 0.7824873:
: :...ALT.1 <= 0.4494382: F4 (4/1)
: : ALT.1 > 0.4494382: F1 (2)
: RNA.Base <= 0.7824873:
: :...WBC > 0.6543359:
: :...Age <= 0.7241379: F3 (5)
: : Age > 0.7241379:
: : :...WBC <= 0.8279912: F3 (3)
: : WBC > 0.8279912:
: : :...ALT.4 <= 0.3370787: F1 (5)
: : ALT.4 > 0.3370787: F3 (3/1)
: WBC <= 0.6543359:
: :...ALT.4 > 0.7865168: F4 (3)
: ALT.4 <= 0.7865168:
: :...ALT.48 <= 0.1910112: F4 (4/1)
: ALT.48 > 0.1910112:
: :...RBC > 0.61062: F1 (3)
: RBC <= 0.61062: [S6]
Age <= 0.5517241:
:...ALT.36 <= 0.01123596:
:...ALT.48 <= 0.6404495: F2 (5)
: ALT.48 > 0.6404495: F4 (2)
ALT.36 > 0.01123596:
:...ALT.36 <= 0.05617978:
:...RNA.Base <= 0.5175647: F3 (5)
: RNA.Base > 0.5175647: F4 (5/1)
ALT.36 > 0.05617978:
:...BMI <= 0.6153846:
:...ALT.24 > 0.8426966: F4 (11/2)
: ALT.24 <= 0.8426966:
: :...RNA.4 <= 0.3422182:
: :...ALT.1 > 0.741573: F1 (5)
: : ALT.1 <= 0.741573:
: : :...ALT.24 <= 0.1685393: F1 (2)
: : ALT.24 > 0.1685393:
: : :...BMI <= 0.5384616: F3 (5/1)
: : BMI > 0.5384616: F2 (5/1)
: RNA.4 > 0.3422182:
: :...Plat <= 0.05295577: F1 (3)
: Plat > 0.05295577:
: :...AST.1 > 0.8651685: F2 (7)
: AST.1 <= 0.8651685:
: :...ALT.1 <= 0.4269663:
: :...Plat > 0.7610209: F2 (5)
: : Plat <= 0.7610209:
: : :...RBC <= 0.4778271: F2 (2)
: : RBC > 0.4778271: F3 (6)
: ALT.1 > 0.4269663:
: :...ALT.48 > 0.8314607: F2 (2)
: ALT.48 <= 0.8314607:
: :...Age <= 0.1724138:
: :...Plat <= 0.5160921: F4 (6)
: : Plat > 0.5160921: F1 (2)
: Age > 0.1724138:
: :...WBC <= 0.3376509: F3 (3/1)
: WBC > 0.3376509: F4 (5/1)
BMI > 0.6153846:
:...AST.1 <= 0.247191:
:...ALT.48 <= 0.2247191:
: :...Age > 0.2068966: F1 (7/1)
: : Age <= 0.2068966:
: : :...ALT.24 <= 0.5280899: F3 (4)
: : ALT.24 > 0.5280899: F2 (4/1)
: ALT.48 > 0.2247191:
: :...Age <= 0.03448276:
: :...ALT.48 > 0.6966292: F2 (3)
: : ALT.48 <= 0.6966292:
: : :...ALT.1 <= 0.6966292: F1 (2)
: : ALT.1 > 0.6966292: F3 (2)
: Age > 0.03448276:
: :...Plat <= 0.1174064: F3 (8/1)
: Plat > 0.1174064:
: :...ALT.24 <= 0.3033708:
: :...Plat <= 0.3844932: F4 (3/1)
: : Plat > 0.3844932: F3 (8)
: ALT.24 > 0.3033708:
: :...ALT.24 <= 0.5955056: F4 (4)
: ALT.24 > 0.5955056:
: :...AST.1 > 0.1460674: F3 (3)
: AST.1 <= 0.1460674:
: :...ALT.12 <= 0.8539326: F4 (6)
: ALT.12 > 0.8539326: F3 (2)
AST.1 > 0.247191:
:...RNA.4 > 0.9682636:
:...AST.1 <= 0.8876405: F2 (5/1)
: AST.1 > 0.8876405: F3 (2)
RNA.4 <= 0.9682636:
:...AST.1 <= 0.2808989:
:...ALT.36 <= 0.7977528: F2 (6/1)
: ALT.36 > 0.7977528: F1 (4/1)
AST.1 > 0.2808989:
:...ALT.24 <= 0.3483146:
:...AST.1 > 0.7078652:
: :...ALT.1 > 0.4269663: F4 (12/1)
: : ALT.1 <= 0.4269663:
: : :...AST.1 <= 0.8988764: F4 (2)
: : AST.1 > 0.8988764: F1 (6/1)
: AST.1 <= 0.7078652:
: :...BMI > 0.9230769: F2 (3/1)
: BMI <= 0.9230769:
: :...ALT.24 <= 0.03370786: F2 (2)
: ALT.24 > 0.03370786:
: :...ALT.12 <= 0.08988764: F4 (4)
: ALT.12 > 0.08988764:
: :...Age <= 0.03448276: F4 (2)
: Age > 0.03448276: [S7]
ALT.24 > 0.3483146:
:...Plat <= 0.1051622:
:...Age <= 0.3103448: F2 (4/1)
: Age > 0.3103448: F4 (4)
Plat > 0.1051622:
:...RNA.Base <= 0.4264929:
:...RBC > 0.903514: F2 (2)
: RBC <= 0.903514:
: :...ALT.24 <= 0.6629214: F1 (8)
: ALT.24 > 0.6629214:
: :...AST.1 > 0.8988764: F1 (4)
: AST.1 <= 0.8988764: [S8]
RNA.Base > 0.4264929:
:...ALT.24 <= 0.4044944: F2 (3)
ALT.24 > 0.4044944:
:...RNA.4 <= 0.3203851: F3 (10/1)
RNA.4 > 0.3203851:
:...RBC > 0.7659233:
:...BMI <= 0.9230769: F3 (4)
: BMI > 0.9230769: F1 (2/1)
RBC <= 0.7659233:
:...WBC > 0.4096597: [S9]
WBC <= 0.4096597: [S10]
SubTree [S1]
ALT.36 <= 0.494382: F4 (3/1)
ALT.36 > 0.494382: F2 (5)
SubTree [S2]
ALT.4 <= 0.3707865: F3 (2)
ALT.4 > 0.3707865: F2 (3/1)
SubTree [S3]
ALT.after.24.w <= 0.1304348: F4 (2)
ALT.after.24.w > 0.1304348: F1 (4/1)
SubTree [S4]
ALT.24 > 0.7865168: F3 (2)
ALT.24 <= 0.7865168:
:...AST.1 <= 0.3483146: F4 (9)
AST.1 > 0.3483146:
:...ALT.after.24.w <= 0.2608696: F3 (2)
ALT.after.24.w > 0.2608696: F4 (5/1)
SubTree [S5]
ALT.after.24.w > 0.7826087: F3 (2)
ALT.after.24.w <= 0.7826087:
:...ALT.12 <= 0.5842696: F2 (6/1)
ALT.12 > 0.5842696:
:...BMI <= 0.2307692: F2 (2/1)
BMI > 0.2307692:
:...ALT.4 <= 0.6629214: F1 (2)
ALT.4 > 0.6629214: F3 (2)
SubTree [S6]
ALT.after.24.w <= 0.8695652: F3 (8/1)
ALT.after.24.w > 0.8695652: F1 (4/1)
SubTree [S7]
ALT.1 <= 0.3258427: F3 (3/1)
ALT.1 > 0.3258427:
:...ALT.36 <= 0.6853933: F1 (7)
ALT.36 > 0.6853933: F3 (3/1)
SubTree [S8]
AST.1 <= 0.3483146: F1 (2)
AST.1 > 0.3483146: F3 (11/2)
SubTree [S9]
RNA.Base <= 0.7343804: F2 (3)
RNA.Base > 0.7343804: F1 (5/1)
SubTree [S10]
BMI <= 0.7692308: F4 (2)
BMI > 0.7692308:
:...AST.1 <= 0.741573: F4 (2)
AST.1 > 0.741573: F2 (2)
Evaluation on training data (968 cases):
Decision Tree
----------------
Size Errors
229 106(11.0%) <<
(a) (b) (c) (d) <-classified as
---- ---- ---- ----
207 7 7 14 (a): class F1
8 211 5 8 (b): class F2
14 10 218 7 (c): class F3
13 6 7 226 (d): class F4
Attribute usage:
100.00% BMI
78.00% Age
75.83% AST.1
75.31% Plat
60.23% RNA.4
58.06% ALT.36
48.24% ALT.after.24.w
47.73% ALT.12
47.52% ALT.24
46.18% ALT.1
39.88% RBC
35.74% ALT.48
27.38% ALT.4
17.56% WBC
16.53% RNA.Base
Time: 0.0 secs
#ggplot(modelo_C5.0Tree, highlight = TRUE) +
# labs(title = "Evolución del accuracy del modelo") +
#theme_bw()
# Predicciones
predicciones_C5.0Tree <- predict(modelo_C5.0Tree, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_C5.0Tree <- caret::confusionMatrix(factor(predicciones_C5.0Tree, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_C5.0Tree
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 25 21 19 30
F2 17 24 30 24
F3 31 27 24 27
F4 27 27 33 27
Overall Statistics
Accuracy : 0.2421
95% CI : (0.2016, 0.2864)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.8292
Kappa : -0.0115
Mcnemar's Test P-Value : 0.6236
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.25000 0.24242 0.22642 0.25000
Specificity 0.77636 0.77389 0.72313 0.71475
Pos Pred Value 0.26316 0.25263 0.22018 0.23684
Neg Pred Value 0.76415 0.76415 0.73026 0.72910
Prevalence 0.24213 0.23971 0.25666 0.26150
Detection Rate 0.06053 0.05811 0.05811 0.06538
Detection Prevalence 0.23002 0.23002 0.26392 0.27603
Balanced Accuracy 0.51318 0.50815 0.47477 0.48238
stats_class_C5.0Tree <- data.frame(model = "C5.0Tree",
precision = conf_mat_C5.0Tree$overall["Accuracy"],
FN = conf_mat_C5.0Tree$table[2,1],
FP = conf_mat_C5.0Tree$table[1,2],
error.rate = 1 - conf_mat_C5.0Tree$overall["Accuracy"],
kappa = conf_mat_C5.0Tree$overall["Kappa"],
sensibilidad = mean(conf_mat_C5.0Tree$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_C5.0Tree$byClass[,"Specificity"]),
precisión = mean(conf_mat_C5.0Tree$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_C5.0Tree$byClass[,"Recall"]),
f.medida = mean(conf_mat_C5.0Tree$byClass[,"F1"])
)
stats_class_C5.0Tree
model precision FN FP error.rate kappa sensibilidad
Accuracy C5.0Tree 0.2421308 17 21 0.7578692 -0.01151035 0.2422098
especificidad precisión recuperación f.medida
Accuracy 0.7470311 0.2432038 0.2422098 0.242583
Generamos el modelo C5.0.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- expand.grid(trials = c(15:20),
model = "tree",
winnow = c(FALSE))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_C5.0 <- caret::train(BH.staging ~ ., data = data_tn,
method = "C5.0",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train)
modelo_C5.0
C5.0
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
trials Accuracy Kappa
15 0.2251110 -0.03415999
16 0.2282371 -0.03002798
17 0.2246499 -0.03485805
18 0.2267852 -0.03207986
19 0.2271063 -0.03160798
20 0.2251228 -0.03427994
Tuning parameter 'model' was held constant at a value of tree
Tuning
parameter 'winnow' was held constant at a value of FALSE
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were trials = 16, model = tree and winnow
= FALSE.
summary(modelo_C5.0$finalModel)
Call:
(function (x, y, trials = 1, rules = FALSE, weights = NULL, control
fuzzyThreshold = FALSE, sample = 0, earlyStopping = TRUE, label =
"outcome", seed = 680L))
C5.0 [Release 2.07 GPL Edition] Mon Apr 24 12:25:33 2023
-------------------------------
Class specified by attribute `outcome'
Read 968 cases (16 attributes) from undefined.data
----- Trial 0: -----
Decision tree:
BMI <= 0.4615385:
:...AST.1 > 0.7640449:
: :...ALT.1 <= 0.05617978:
: : :...RBC <= 0.6272686: F3 (6)
: : : RBC > 0.6272686: F1 (4)
: : ALT.1 > 0.05617978:
: : :...ALT.48 <= 0.08988764:
: : :...RNA.4 <= 0.4694727:
: : : :...ALT.4 <= 0.5168539: F4 (4/1)
: : : : ALT.4 > 0.5168539: F3 (2)
: : : RNA.4 > 0.4694727:
: : : :...RBC <= 0.7754056: F2 (4/1)
: : : RBC > 0.7754056: F4 (4)
: : ALT.48 > 0.08988764:
: : :...RNA.4 > 0.8480108:
: : :...ALT.24 <= 0.6179775: F4 (2)
: : : ALT.24 > 0.6179775:
: : : :...WBC <= 0.6020856: F1 (6/1)
: : : WBC > 0.6020856: F3 (2)
: : RNA.4 <= 0.8480108:
: : :...Age > 0.4827586:
: : :...RBC > 0.8265383: F3 (3/1)
: : : RBC <= 0.8265383:
: : : :...ALT.12 <= 0.3033708: F3 (9/1)
: : : ALT.12 > 0.3033708:
: : : :...Plat > 0.6226405: F2 (13)
: : : Plat <= 0.6226405:
: : : :...ALT.1 > 0.6179775: F3 (5)
: : : ALT.1 <= 0.6179775:
: : : :...ALT.1 <= 0.4269663: F3 (2)
: : : ALT.1 > 0.4269663: F2 (4)
: : Age <= 0.4827586:
: : :...ALT.36 > 0.7865168:
: : :...BMI <= 0.1538462: F4 (4/1)
: : : BMI > 0.1538462: F3 (3)
: : ALT.36 <= 0.7865168:
: : :...ALT.after.24.w > 0.7826087: F2 (4)
: : ALT.after.24.w <= 0.7826087:
: : :...Age > 0.3448276:
: : :...RNA.Base <= 0.6924855: F1 (5/1)
: : : RNA.Base > 0.6924855: F4 (4/1)
: : Age <= 0.3448276:
: : :...ALT.1 > 0.752809: F1 (3/1)
: : ALT.1 <= 0.752809:
: : :...RNA.4 <= 0.373249: F1 (3/1)
: : RNA.4 > 0.373249:
: : :...ALT.24 <= 0.7191011: F2 (8/1)
: : ALT.24 > 0.7191011: F3 (2)
: AST.1 <= 0.7640449:
: :...ALT.12 <= 0.04494382:
: :...ALT.after.24.w <= 0.08695652: F2 (3/1)
: : ALT.after.24.w > 0.08695652:
: : :...RBC <= 0.4163593: F1 (3/1)
: : RBC > 0.4163593:
: : :...ALT.4 <= 0.2134831: F1 (3/1)
: : ALT.4 > 0.2134831: F3 (8)
: ALT.12 > 0.04494382:
: :...ALT.after.24.w <= 0.4782609:
: :...Age <= 0.06896552:
: : :...Plat > 0.6581442: F1 (4)
: : : Plat <= 0.6581442:
: : : :...Plat > 0.4399442: F4 (4)
: : : Plat <= 0.4399442:
: : : :...Age > 0.03448276: F4 (2)
: : : Age <= 0.03448276:
: : : :...ALT.1 <= 0.6853933: F1 (7/1)
: : : ALT.1 > 0.6853933: F4 (3/1)
: : Age > 0.06896552:
: : :...ALT.36 <= 0.08988764:
: : :...RNA.Base <= 0.3228641: F2 (4)
: : : RNA.Base > 0.3228641: F4 (4/1)
: : ALT.36 > 0.08988764:
: : :...Plat <= 0.05252864:
: : :...ALT.1 <= 0.1460674: F3 (3)
: : : ALT.1 > 0.1460674: F2 (3)
: : Plat > 0.05252864:
: : :...ALT.1 > 0.752809:
: : :...RNA.4 > 0.7888218:
: : : :...Age <= 0.4137931: F2 (5)
: : : : Age > 0.4137931: F1 (3/1)
: : : RNA.4 <= 0.7888218:
: : : :...RBC <= 0.3398761: F3 (5/1)
: : : RBC > 0.3398761:
: : : :...ALT.24 <= 0.1011236: F3 (2)
: : : ALT.24 > 0.1011236:
: : : :...ALT.4 <= 0.1573034: F2 (2)
: : : ALT.4 > 0.1573034:
: : : :...ALT.48 <= 0.6516854: F1 (14/1)
: : : ALT.48 > 0.6516854:
: : : :...WBC > 0.4070252: F4 (4)
: : : WBC <= 0.4070252:
: : : :...Age <= 0.6896552: F2 (2)
: : : Age > 0.6896552: F1 (2)
: : ALT.1 <= 0.752809:
: : :...ALT.4 > 0.9325843: F2 (5/1)
: : ALT.4 <= 0.9325843:
: : :...Plat > 0.812478:
: : :...RNA.4 <= 0.2695684:
: : : :...WBC <= 0.3960483: F4 (2)
: : : : WBC > 0.3960483: F3 (3)
: : : RNA.4 > 0.2695684:
: : : :...ALT.4 <= 0.7191011:
: : : :...WBC <= 0.2881449: F3 (2)
: : : : WBC > 0.2881449: F1 (9/1)
: : : ALT.4 > 0.7191011:
: : : :...WBC <= 0.5615807: F1 (2)
: : : WBC > 0.5615807: F4 (2)
: : Plat <= 0.812478:
: : :...ALT.12 <= 0.4831461:
: : :...RNA.4 <= 0.1410989: F4 (5)
: : : RNA.4 > 0.1410989:
: : : :...Plat <= 0.1263235: F1 (3/1)
: : : Plat > 0.1263235:
: : : :...WBC > 0.5037321:
: : : :...ALT.12 <= 0.2134831: F4 (2)
: : : : ALT.12 > 0.2134831: [S1]
: : : WBC <= 0.5037321:
: : : :...ALT.48 > 0.8089887: F2 (3)
: : : ALT.48 <= 0.8089887:
: : : :...ALT.1 <= 0.3033708: [S2]
: : : ALT.1 > 0.3033708: [S3]
: : ALT.12 > 0.4831461:
: : :...Plat > 0.6268818:
: : :...RNA.4 <= 0.1373751: F2 (2)
: : : RNA.4 > 0.1373751: F4 (14/2)
: : Plat <= 0.6268818:
: : :...ALT.12 > 0.7865168:
: : :...RBC <= 0.8629725: F1 (7)
: : : RBC > 0.8629725: F3 (2)
: : ALT.12 <= 0.7865168:
: : :...ALT.24 > 0.8426966:
: : :...ALT.12 <= 0.5842696: F1 (3)
: : : ALT.12 > 0.5842696: F4 (2)
: : ALT.24 <= 0.8426966:
: : :...RNA.Base <= 0.1421885: F3 (3)
: : RNA.Base > 0.1421885: [S4]
: ALT.after.24.w > 0.4782609:
: :...ALT.12 > 0.7640449:
: :...ALT.after.24.w > 0.9565217:
: : :...ALT.36 <= 0.4269663: F3 (3)
: : : ALT.36 > 0.4269663:
: : : :...Age <= 0.1724138: F3 (2)
: : : Age > 0.1724138: F4 (2)
: : ALT.after.24.w <= 0.9565217:
: : :...WBC > 0.8446762:
: : :...ALT.24 <= 0.3820225: F1 (2)
: : : ALT.24 > 0.3820225: F3 (4)
: : WBC <= 0.8446762:
: : :...Plat > 0.8774456: F1 (4)
: : Plat <= 0.8774456:
: : :...ALT.4 <= 0.3820225:
: : :...WBC <= 0.8316136: F1 (8/1)
: : : WBC > 0.8316136: F4 (2)
: : ALT.4 > 0.3820225:
: : :...RBC <= 0.1343212: F3 (3/1)
: : RBC > 0.1343212: F4 (12/1)
: ALT.12 <= 0.7640449:
: :...RBC > 0.8252838:
: :...Plat <= 0.5872193:
: : :...ALT.after.24.w <= 0.8695652: F3 (8/1)
: : : ALT.after.24.w > 0.8695652: F1 (4/1)
: : Plat > 0.5872193:
: : :...ALT.24 > 0.2808989: F2 (10/2)
: : ALT.24 <= 0.2808989:
: : :...RBC <= 0.8555975: F3 (2)
: : RBC > 0.8555975: F4 (2)
: RBC <= 0.8252838:
: :...AST.1 <= 0.07865169:
: :...ALT.4 <= 0.8764045: F4 (13/2)
: : ALT.4 > 0.8764045: F1 (2)
: AST.1 > 0.07865169:
: :...ALT.24 > 0.6629214:
: :...ALT.36 > 0.5168539: F4 (14/4)
: : ALT.36 <= 0.5168539:
: : :...ALT.after.24.w <= 0.8260869:
: : :...AST.1 <= 0.3370787: F3 (3)
: : : AST.1 > 0.3370787: F1 (5/1)
: : ALT.after.24.w > 0.8260869:
: : :...RNA.Base <= 0.2988623: F1 (2/1)
: : RNA.Base > 0.2988623: F4 (6/1)
: ALT.24 <= 0.6629214:
: :...ALT.12 <= 0.4269663:
: :...ALT.1 <= 0.4157303:
: : :...RBC > 0.3016891: F3 (7/1)
: : : RBC <= 0.3016891:
: : : :...WBC <= 0.5536773: F1 (3)
: : : WBC > 0.5536773: F2 (2)
: : ALT.1 > 0.4157303:
: : :...Age <= 0.5517241: F1 (9/2)
: : Age > 0.5517241:
: : :...ALT.1 <= 0.8539326: F4 (6/1)
: : ALT.1 > 0.8539326: F3 (2)
: ALT.12 > 0.4269663:
: :...ALT.48 <= 0.4494382:
: :...ALT.4 > 0.9101124: F3 (2)
: : ALT.4 <= 0.9101124:
: : :...ALT.after.24.w <= 0.9130435: F4 (11/2)
: : ALT.after.24.w > 0.9130435: F2 (2)
: ALT.48 > 0.4494382:
: :...ALT.36 <= 0.02247191: F4 (2)
: ALT.36 > 0.02247191:
: :...ALT.24 > 0.505618:
: :...Age <= 0.3448276: F4 (2)
: : Age > 0.3448276: F2 (2)
: ALT.24 <= 0.505618:
: :...ALT.after.24.w > 0.8260869:
: :...ALT.12 <= 0.5505618: F2 (3)
: : ALT.12 > 0.5505618: F1 (3/1)
: ALT.after.24.w <= 0.8260869:
: :...ALT.36 > 0.6629214: F3 (4)
: ALT.36 <= 0.6629214: [S5]
BMI > 0.4615385:
:...Plat > 0.971068:
:...Age <= 0.5862069: F2 (7/1)
: Age > 0.5862069:
: :...ALT.12 <= 0.6292135: F3 (4/1)
: ALT.12 > 0.6292135: F2 (2)
Plat <= 0.971068:
:...Age > 0.5517241:
:...RNA.4 <= 0.4070092:
: :...BMI <= 0.5384616:
: : :...RNA.4 <= 0.04654451: F1 (2)
: : : RNA.4 > 0.04654451:
: : : :...RNA.4 > 0.2394163: F4 (2)
: : : RNA.4 <= 0.2394163:
: : : :...Age <= 0.6896552: F2 (3/1)
: : : Age > 0.6896552: F3 (4)
: : BMI > 0.5384616:
: : :...ALT.48 > 0.741573:
: : :...Age <= 0.7586207:
: : : :...ALT.1 <= 0.8089887: F4 (6)
: : : : ALT.1 > 0.8089887: F1 (2)
: : : Age > 0.7586207:
: : : :...RBC <= 0.2869931: F1 (3/1)
: : : RBC > 0.2869931: F2 (5/1)
: : ALT.48 <= 0.741573:
: : :...Age > 0.7931035:
: : :...ALT.after.24.w <= 0.04347826: F1 (2)
: : : ALT.after.24.w > 0.04347826:
: : : :...AST.1 <= 0.5168539: F2 (10)
: : : AST.1 > 0.5168539:
: : : :...ALT.24 <= 0.2696629: F3 (3/1)
: : : ALT.24 > 0.2696629: F2 (7/2)
: : Age <= 0.7931035:
: : :...ALT.24 > 0.9101124: F1 (4/1)
: : ALT.24 <= 0.9101124:
: : :...ALT.36 > 0.3707865:
: : :...RNA.4 <= 0.3351882: F2 (14/1)
: : : RNA.4 > 0.3351882: F1 (3/1)
: : ALT.36 <= 0.3707865:
: : :...BMI > 0.9230769: F1 (2/1)
: : BMI <= 0.9230769:
: : :...Plat <= 0.394347: F4 (3)
: : Plat > 0.394347: F1 (5/1)
: RNA.4 > 0.4070092:
: :...Plat > 0.8752651:
: :...BMI <= 0.6923077: F1 (2/1)
: : BMI > 0.6923077: F2 (6)
: Plat <= 0.8752651:
: :...BMI > 0.7692308:
: :...ALT.1 <= 0.3932584:
: : :...BMI <= 0.8461539:
: : : :...ALT.24 <= 0.5280899: F1 (3/1)
: : : : ALT.24 > 0.5280899: F2 (5)
: : : BMI > 0.8461539:
: : : :...ALT.after.24.w <= 0.6521739:
: : : :...ALT.4 <= 0.7191011: F3 (8/1)
: : : : ALT.4 > 0.7191011: F1 (4)
: : : ALT.after.24.w > 0.6521739:
: : : :...ALT.1 <= 0.3033708: F2 (5/1)
: : : ALT.1 > 0.3033708: F1 (2)
: : ALT.1 > 0.3932584:
: : :...ALT.1 <= 0.7752809:
: : :...WBC <= 0.2667398: F2 (3/1)
: : : WBC > 0.2667398: F4 (7/1)
: : ALT.1 > 0.7752809:
: : :...Plat <= 0.3123768: F2 (2)
: : Plat > 0.3123768:
: : :...ALT.4 > 0.1235955: F3 (6)
: : ALT.4 <= 0.1235955:
: : :...Plat <= 0.6354542: F4 (3)
: : Plat > 0.6354542: F1 (2/1)
: BMI <= 0.7692308:
: :...RBC > 0.917794:
: :...ALT.12 <= 0.4831461: F2 (3)
: : ALT.12 > 0.4831461: F1 (2/1)
: RBC <= 0.917794:
: :...Age <= 0.5862069:
: :...ALT.12 > 0.5955056: F3 (2)
: : ALT.12 <= 0.5955056:
: : :...ALT.4 <= 0.752809: F1 (2/1)
: : ALT.4 > 0.752809: F2 (2)
: Age > 0.5862069:
: :...RNA.Base > 0.7824873:
: :...ALT.1 <= 0.4494382: F4 (4/1)
: : ALT.1 > 0.4494382: F1 (2)
: RNA.Base <= 0.7824873:
: :...WBC > 0.6543359:
: :...Age <= 0.7241379: F3 (5)
: : Age > 0.7241379:
: : :...WBC <= 0.8279912: F3 (3)
: : WBC > 0.8279912:
: : :...ALT.4 <= 0.3370787: F1 (5)
: : ALT.4 > 0.3370787: F3 (3/1)
: WBC <= 0.6543359:
: :...ALT.4 > 0.7865168: F4 (3)
: ALT.4 <= 0.7865168:
: :...ALT.48 <= 0.1910112: F4 (4/1)
: ALT.48 > 0.1910112:
: :...RBC > 0.61062: F1 (3)
: RBC <= 0.61062: [S6]
Age <= 0.5517241:
:...ALT.36 <= 0.01123596:
:...ALT.48 <= 0.6404495: F2 (5)
: ALT.48 > 0.6404495: F4 (2)
ALT.36 > 0.01123596:
:...ALT.36 <= 0.05617978:
:...RNA.Base <= 0.5175647: F3 (5)
: RNA.Base > 0.5175647: F4 (5/1)
ALT.36 > 0.05617978:
:...BMI <= 0.6153846:
:...ALT.24 > 0.8426966: F4 (11/2)
: ALT.24 <= 0.8426966:
: :...RNA.4 <= 0.3422182:
: :...ALT.1 > 0.741573: F1 (5)
: : ALT.1 <= 0.741573:
: : :...ALT.24 <= 0.1685393: F1 (2)
: : ALT.24 > 0.1685393:
: : :...BMI <= 0.5384616: F3 (5/1)
: : BMI > 0.5384616: F2 (5/1)
: RNA.4 > 0.3422182:
: :...Plat <= 0.05295577: F1 (3)
: Plat > 0.05295577:
: :...AST.1 > 0.8651685: F2 (7)
: AST.1 <= 0.8651685:
: :...ALT.1 <= 0.4269663:
: :...Plat > 0.7610209: F2 (5)
: : Plat <= 0.7610209:
: : :...RBC <= 0.4778271: F2 (2)
: : RBC > 0.4778271: F3 (6)
: ALT.1 > 0.4269663:
: :...ALT.48 > 0.8314607: F2 (2)
: ALT.48 <= 0.8314607:
: :...Age <= 0.1724138:
: :...Plat <= 0.5160921: F4 (6)
: : Plat > 0.5160921: F1 (2)
: Age > 0.1724138:
: :...WBC <= 0.3376509: F3 (3/1)
: WBC > 0.3376509: F4 (5/1)
BMI > 0.6153846:
:...AST.1 <= 0.247191:
:...ALT.48 <= 0.2247191:
: :...Age > 0.2068966: F1 (7/1)
: : Age <= 0.2068966:
: : :...ALT.24 <= 0.5280899: F3 (4)
: : ALT.24 > 0.5280899: F2 (4/1)
: ALT.48 > 0.2247191:
: :...Age <= 0.03448276:
: :...ALT.48 > 0.6966292: F2 (3)
: : ALT.48 <= 0.6966292:
: : :...ALT.1 <= 0.6966292: F1 (2)
: : ALT.1 > 0.6966292: F3 (2)
: Age > 0.03448276:
: :...Plat <= 0.1174064: F3 (8/1)
: Plat > 0.1174064:
: :...ALT.24 <= 0.3033708:
: :...Plat <= 0.3844932: F4 (3/1)
: : Plat > 0.3844932: F3 (8)
: ALT.24 > 0.3033708:
: :...ALT.24 <= 0.5955056: F4 (4)
: ALT.24 > 0.5955056:
: :...AST.1 > 0.1460674: F3 (3)
: AST.1 <= 0.1460674:
: :...ALT.12 <= 0.8539326: F4 (6)
: ALT.12 > 0.8539326: F3 (2)
AST.1 > 0.247191:
:...RNA.4 > 0.9682636:
:...AST.1 <= 0.8876405: F2 (5/1)
: AST.1 > 0.8876405: F3 (2)
RNA.4 <= 0.9682636:
:...AST.1 <= 0.2808989:
:...ALT.36 <= 0.7977528: F2 (6/1)
: ALT.36 > 0.7977528: F1 (4/1)
AST.1 > 0.2808989:
:...ALT.24 <= 0.3483146:
:...AST.1 > 0.7078652:
: :...ALT.1 > 0.4269663: F4 (12/1)
: : ALT.1 <= 0.4269663:
: : :...AST.1 <= 0.8988764: F4 (2)
: : AST.1 > 0.8988764: F1 (6/1)
: AST.1 <= 0.7078652:
: :...BMI > 0.9230769: F2 (3/1)
: BMI <= 0.9230769:
: :...ALT.24 <= 0.03370786: F2 (2)
: ALT.24 > 0.03370786:
: :...ALT.12 <= 0.08988764: F4 (4)
: ALT.12 > 0.08988764:
: :...Age <= 0.03448276: F4 (2)
: Age > 0.03448276: [S7]
ALT.24 > 0.3483146:
:...Plat <= 0.1051622:
:...Age <= 0.3103448: F2 (4/1)
: Age > 0.3103448: F4 (4)
Plat > 0.1051622:
:...RNA.Base <= 0.4264929:
:...RBC > 0.903514: F2 (2)
: RBC <= 0.903514:
: :...ALT.24 <= 0.6629214: F1 (8)
: ALT.24 > 0.6629214:
: :...AST.1 > 0.8988764: F1 (4)
: AST.1 <= 0.8988764: [S8]
RNA.Base > 0.4264929:
:...ALT.24 <= 0.4044944: F2 (3)
ALT.24 > 0.4044944:
:...RNA.4 <= 0.3203851: F3 (10/1)
RNA.4 > 0.3203851:
:...RBC > 0.7659233:
:...BMI <= 0.9230769: F3 (4)
: BMI > 0.9230769: F1 (2/1)
RBC <= 0.7659233:
:...WBC > 0.4096597: [S9]
WBC <= 0.4096597: [S10]
SubTree [S1]
ALT.36 <= 0.494382: F4 (3/1)
ALT.36 > 0.494382: F2 (5)
SubTree [S2]
ALT.4 <= 0.3707865: F3 (2)
ALT.4 > 0.3707865: F2 (3/1)
SubTree [S3]
ALT.after.24.w <= 0.1304348: F4 (2)
ALT.after.24.w > 0.1304348: F1 (4/1)
SubTree [S4]
ALT.24 > 0.7865168: F3 (2)
ALT.24 <= 0.7865168:
:...AST.1 <= 0.3483146: F4 (9)
AST.1 > 0.3483146:
:...ALT.after.24.w <= 0.2608696: F3 (2)
ALT.after.24.w > 0.2608696: F4 (5/1)
SubTree [S5]
ALT.after.24.w > 0.7826087: F3 (2)
ALT.after.24.w <= 0.7826087:
:...ALT.12 <= 0.5842696: F2 (6/1)
ALT.12 > 0.5842696:
:...BMI <= 0.2307692: F2 (2/1)
BMI > 0.2307692:
:...ALT.4 <= 0.6629214: F1 (2)
ALT.4 > 0.6629214: F3 (2)
SubTree [S6]
ALT.after.24.w <= 0.8695652: F3 (8/1)
ALT.after.24.w > 0.8695652: F1 (4/1)
SubTree [S7]
ALT.1 <= 0.3258427: F3 (3/1)
ALT.1 > 0.3258427:
:...ALT.36 <= 0.6853933: F1 (7)
ALT.36 > 0.6853933: F3 (3/1)
SubTree [S8]
AST.1 <= 0.3483146: F1 (2)
AST.1 > 0.3483146: F3 (11/2)
SubTree [S9]
RNA.Base <= 0.7343804: F2 (3)
RNA.Base > 0.7343804: F1 (5/1)
SubTree [S10]
BMI <= 0.7692308: F4 (2)
BMI > 0.7692308:
:...AST.1 <= 0.741573: F4 (2)
AST.1 > 0.741573: F2 (2)
----- Trial 1: -----
Decision tree:
ALT.48 > 0.9438202:
:...WBC <= 0.06355653:
: :...BMI <= 0.6153846: F2 (10.7/1.6)
: : BMI > 0.6153846: F3 (2.3)
: WBC > 0.06355653:
: :...WBC > 0.9231614: F2 (3.6)
: WBC <= 0.9231614:
: :...ALT.4 <= 0.1460674: F3 (5.5/2.3)
: ALT.4 > 0.1460674:
: :...ALT.after.24.w > 0.7391304:
: :...ALT.1 <= 0.7752809: F3 (6.2/2.3)
: : ALT.1 > 0.7752809: F4 (3.6)
: ALT.after.24.w <= 0.7391304:
: :...ALT.48 <= 0.9662921: F2 (12.5/5.5)
: ALT.48 > 0.9662921:
: :...Plat <= 0.8756548: F4 (12.2/1.6)
: Plat > 0.8756548: F1 (2.3/0.8)
ALT.48 <= 0.9438202:
:...ALT.4 > 0.9213483:
:...ALT.48 > 0.7640449: F1 (11/0.8)
: ALT.48 <= 0.7640449:
: :...BMI > 0.6923077:
: :...RNA.4 <= 0.1295362: F1 (5.6)
: : RNA.4 > 0.1295362: F2 (6.2)
: BMI <= 0.6923077:
: :...RNA.4 <= 0.2307412:
: :...ALT.36 <= 0.5280899: F4 (12.3/1.6)
: : ALT.36 > 0.5280899: F1 (3.9/1.6)
: RNA.4 > 0.2307412:
: :...AST.1 > 0.8876405: F2 (2.3)
: AST.1 <= 0.8876405:
: :...ALT.after.24.w > 0.7391304: F3 (6.2/1.6)
: ALT.after.24.w <= 0.7391304:
: :...ALT.36 > 0.7865168: F3 (4.7/2.3)
: ALT.36 <= 0.7865168:
: :...Plat > 0.7179264: F2 (4.7/0.8)
: Plat <= 0.7179264:
: :...ALT.1 <= 0.4044944: F1 (5.1)
: ALT.1 > 0.4044944: F4 (4.7/1.6)
ALT.4 <= 0.9213483:
:...ALT.after.24.w > 0.8260869:
:...ALT.36 > 0.8764045:
: :...BMI <= 0: F1 (2.8)
: : BMI > 0:
: : :...WBC <= 0.4088913: F4 (6.7/1.6)
: : WBC > 0.4088913:
: : :...AST.1 <= 0.3932584: F4 (3.1)
: : AST.1 > 0.3932584: F2 (5.5/0.8)
: ALT.36 <= 0.8764045:
: :...ALT.after.24.w > 0.9565217:
: :...ALT.48 > 0.741573: F1 (3.1)
: : ALT.48 <= 0.741573:
: : :...WBC <= 0.3937431:
: : :...RNA.4 <= 0.4928535: F3 (13)
: : : RNA.4 > 0.4928535: F2 (5.5/2.3)
: : WBC > 0.3937431:
: : :...Age <= 0.7586207: F4 (12.2/3.9)
: : Age > 0.7586207: F3 (2.3)
: ALT.after.24.w <= 0.9565217:
: :...WBC <= 0.0273326: F3 (3.6)
: WBC > 0.0273326:
: :...AST.1 > 0.6404495:
: :...RNA.Base <= 0.3474912:
: : :...ALT.after.24.w <= 0.9130435: F1 (10.3/0.8)
: : : ALT.after.24.w > 0.9130435: F3 (2.3/0.8)
: : RNA.Base > 0.3474912:
: : :...RNA.4 <= 0.6511205: F3 (12.2/3.1)
: : RNA.4 > 0.6511205: F4 (7/3.1)
: AST.1 <= 0.6404495:
: :...RNA.Base > 0.8249535:
: :...ALT.4 <= 0.5168539: F1 (13.8/0.8)
: : ALT.4 > 0.5168539: F4 (3.9/1.6)
: RNA.Base <= 0.8249535:
: :...ALT.48 > 0.8651685: F2 (5.9/0.8)
: ALT.48 <= 0.8651685:
: :...AST.1 > 0.4269663: F4 (12.6/1.6)
: AST.1 <= 0.4269663:
: :...Age > 0.7241379: F1 (7.5/1.6)
: Age <= 0.7241379:
: :...ALT.4 <= 0.2134831: F1 (5.5/2.3)
: ALT.4 > 0.2134831:
: :...ALT.12 > 0.6067415: F4 (6.2/3.1)
: ALT.12 <= 0.6067415:
: :...ALT.36 <= 0.5168539: F2 (3.9/0.8)
: ALT.36 > 0.5168539: F3 (3.9/0.8)
ALT.after.24.w <= 0.8260869:
:...ALT.36 <= 0.02247191:
:...ALT.36 <= 0.01123596:
: :...ALT.12 <= 0.1910112: F1 (2.3/0.8)
: : ALT.12 > 0.1910112: F2 (12.2/1.6)
: ALT.36 > 0.01123596:
: :...ALT.48 <= 0.505618: F3 (5.5/1.6)
: ALT.48 > 0.505618: F4 (2.3/0.8)
ALT.36 > 0.02247191:
:...ALT.12 > 0.8876405:
:...WBC > 0.8140505:
: :...ALT.48 <= 0.4382023: F2 (6.3/0.8)
: : ALT.48 > 0.4382023: F3 (5.5/0.8)
: WBC <= 0.8140505:
: :...BMI > 0.9230769: F1 (5.9)
: BMI <= 0.9230769:
: :...WBC > 0.556202:
: :...ALT.after.24.w <= 0.6086956: F1 (13.4/1.6)
: : ALT.after.24.w > 0.6086956: F4 (3.1/0.8)
: WBC <= 0.556202:
: :...RNA.Base <= 0.295656: F4 (10.1/3.9)
: RNA.Base > 0.295656:
: :...ALT.after.24.w > 0.4782609: F1 (7/1.6)
: ALT.after.24.w <= 0.4782609:
: :...ALT.4 <= 0.5617977:
: :...ALT.24 <= 0.6853933: F2 (6.2/1.6)
: : ALT.24 > 0.6853933: F3 (3.1/0.8)
: ALT.4 > 0.5617977:
: :...ALT.24 <= 0.741573: F3 (6.2/1.6)
: ALT.24 > 0.741573: F1 (2.3)
ALT.12 <= 0.8876405:
:...ALT.12 > 0.8089887:
:...AST.1 <= 0.1348315: F1 (3.1/0.8)
: AST.1 > 0.1348315:
: :...ALT.36 <= 0.5955056:
: :...RBC <= 0.3472113: F3 (4.3)
: : RBC > 0.3472113:
: : :...ALT.1 <= 0.3033708: F4 (3.9/1.6)
: : ALT.1 > 0.3033708: F2 (19.7/1.6)
: ALT.36 > 0.5955056:
: :...BMI > 0.5384616: F2 (7/3.9)
: BMI <= 0.5384616:
: :...ALT.36 <= 0.7078652: F1 (2.3/0.8)
: ALT.36 > 0.7078652:
: :...ALT.24 > 0.8089887: F4 (3.1/0.8)
: ALT.24 <= 0.8089887:
: :...ALT.36 <= 0.9101124: F3 (8.7)
: ALT.36 > 0.9101124: F4 (3.1/0.8)
ALT.12 <= 0.8089887:
:...ALT.36 <= 0.1910112:
:...Age > 0.8965517:
: :...ALT.24 <= 0.5842696: F1 (5.9/0.8)
: : ALT.24 > 0.5842696: F2 (5.5/2.3)
: Age <= 0.8965517:
: :...ALT.36 <= 0.05617978:
: :...ALT.4 <= 0.1685393: F3 (3.9/1.6)
: : ALT.4 > 0.1685393: F4 (9/0.8)
: ALT.36 > 0.05617978:
: :...AST.1 <= 0.06741573:
: :...ALT.36 <= 0.1685393: F4 (5.9)
: : ALT.36 > 0.1685393: F1 (2.3)
: AST.1 > 0.06741573:
: :...RNA.4 <= 0.171692:
: :...Age > 0.4827586: F4 (3.1)
: : Age <= 0.4827586:
: : :...ALT.4 <= 0.8314607: F1 (4.7/0.8)
: : ALT.4 > 0.8314607: F3 (2.3/0.8)
: RNA.4 > 0.171692:
: :...ALT.12 <= 0.3033708:
: :...ALT.after.24.w <= 0.2173913: F1 (5.5/2.3)
: : ALT.after.24.w > 0.2173913:
: : :...ALT.24 <= 0.4157303: F3 (4.7/1.6)
: : ALT.24 > 0.4157303: F2 (4.7)
: ALT.12 > 0.3033708:
: :...ALT.24 > 0.8764045: F4 (5.1/1.6)
: ALT.24 <= 0.8764045:
: :...RBC <= 0.3201445: F2 (8.2/1.6)
: RBC > 0.3201445:
: :...Age > 0.7586207: F4 (2.3/0.8)
: Age <= 0.7586207:
: :...BMI <= 0.3846154: F2 (5.1)
: BMI > 0.3846154: [S1]
ALT.36 > 0.1910112:
:...ALT.36 <= 0.2022472: F3 (11.8/2.3)
ALT.36 > 0.2022472:
:...ALT.24 > 0.9775281:
:...AST.1 <= 0.7191011: F2 (8.7/0.8)
: AST.1 > 0.7191011: F3 (2.3/0.8)
ALT.24 <= 0.9775281:
:...ALT.36 > 0.9662921:
:...AST.1 <= 0.6966292: F1 (13.4/3.1)
: AST.1 > 0.6966292: F3 (6.7/1.6)
ALT.36 <= 0.9662921:
:...AST.1 > 0.988764:
:...RBC <= 0.2635369: F2 (2.3/0.8)
: RBC > 0.2635369: F4 (7.9/0.8)
AST.1 <= 0.988764:
:...ALT.48 <= 0.08988764:
:...AST.1 <= 0.1235955: F3 (3.6)
: AST.1 > 0.1235955:
: :...ALT.1 <= 0.1460674: F1 (9.5/2.3)
: ALT.1 > 0.1460674:
: :...Age > 0.7241379: F4 (8.7)
: Age <= 0.7241379: [S2]
ALT.48 > 0.08988764:
:...ALT.after.24.w <= 0.1304348:
:...ALT.36 > 0.6741573:
: :...ALT.12 > 0.6516854: F2 (7.1)
: : ALT.12 <= 0.6516854:
: : :...BMI > 0.4615385: F3 (11.4/2.3)
: : BMI <= 0.4615385: [S3]
: ALT.36 <= 0.6741573:
: :...Age <= 0.03448276: F1 (4.3/0.8)
: Age > 0.03448276: [S4]
ALT.after.24.w > 0.1304348:
:...AST.1 <= 0.1348315:
:...BMI <= 0.1538462: F4 (11/0.8)
: BMI > 0.1538462:
: :...RNA.4 > 0.4756364: [S5]
: RNA.4 <= 0.4756364: [S6]
AST.1 > 0.1348315:
:...ALT.48 <= 0.2134831:
:...WBC > 0.5979144: [S7]
: WBC <= 0.5979144: [S8]
ALT.48 > 0.2134831: [S9]
SubTree [S1]
ALT.36 <= 0.1123596: F2 (5.5/1.6)
ALT.36 > 0.1123596: F4 (6.7/0.8)
SubTree [S2]
ALT.24 > 0.8539326: F1 (3.1/0.8)
ALT.24 <= 0.8539326:
:...ALT.36 > 0.6516854:
:...ALT.24 <= 0.2247191: F1 (3.9/1.6)
: ALT.24 > 0.2247191: F4 (6.2/1.6)
ALT.36 <= 0.6516854:
:...RNA.Base <= 0.08317132: F2 (2.3/0.8)
RNA.Base > 0.08317132:
:...ALT.1 <= 0.6741573: F3 (7/2.3)
ALT.1 > 0.6741573: F4 (4.7)
SubTree [S3]
ALT.4 <= 0.505618: F2 (4.7/2.3)
ALT.4 > 0.505618: F4 (9.5/1.6)
SubTree [S4]
RNA.Base > 0.3891023: F4 (21.2/6.2)
RNA.Base <= 0.3891023:
:...RNA.Base > 0.2514181: F2 (4.7/0.8)
RNA.Base <= 0.2514181:
:...Plat <= 0.3457599: F4 (5.5/2.3)
Plat > 0.3457599: F3 (3.1/0.8)
SubTree [S5]
RNA.4 <= 0.8287466: F3 (12.3)
RNA.4 > 0.8287466: F4 (5.5/2.3)
SubTree [S6]
BMI > 0.4615385: F4 (4.7/0.8)
BMI <= 0.4615385:
:...Plat <= 0.4985126: F1 (2.3/0.8)
Plat > 0.4985126: F2 (6.7/0.8)
SubTree [S7]
ALT.48 <= 0.1685393: F2 (5.5/0.8)
ALT.48 > 0.1685393: F4 (2.3/0.8)
SubTree [S8]
ALT.after.24.w <= 0.3043478: F1 (3.9/2.3)
ALT.after.24.w > 0.3043478:
:...RBC <= 0.05493545: F4 (3.6)
RBC > 0.05493545: F3 (24.5/4.7)
SubTree [S9]
ALT.after.24.w > 0.6956522:
:...ALT.36 > 0.8202247: F1 (8.7/1.6)
: ALT.36 <= 0.8202247:
: :...RNA.4 <= 0.4600195: F2 (11.4/2.3)
: RNA.4 > 0.4600195:
: :...AST.1 <= 0.2359551: F3 (5.1/0.8)
: AST.1 > 0.2359551:
: :...Age > 0.7586207: F1 (3.9/1.6)
: Age <= 0.7586207:
: :...BMI <= 0.2307692: F4 (2.3)
: BMI > 0.2307692:
: :...RNA.4 <= 0.6389204: F4 (2.3/0.8)
: RNA.4 > 0.6389204: F2 (7/3.1)
ALT.after.24.w <= 0.6956522:
:...Age <= 0.03448276: F1 (8.6/2.3)
Age > 0.03448276:
:...ALT.24 > 0.7977528:
:...RBC > 0.9270417: F4 (4.3/0.8)
: RBC <= 0.9270417:
: :...ALT.4 > 0.8651685: F3 (7.1/1.6)
: ALT.4 <= 0.8651685:
: :...ALT.12 <= 0.5393258: F1 (17.3/3.1)
: ALT.12 > 0.5393258: F3 (4.7/0.8)
ALT.24 <= 0.7977528:
:...ALT.4 > 0.741573:
:...AST.1 <= 0.3370787: F3 (3.9/2.3)
: AST.1 > 0.3370787:
: :...RNA.Base > 0.822892: F2 (5.9/0.8)
: RNA.Base <= 0.822892:
: :...WBC > 0.8243688: F1 (9.5/0.8)
: WBC <= 0.8243688:
: :...Plat <= 0.5135443: F1 (6.2/2.3)
: Plat > 0.5135443: F2 (3.1)
ALT.4 <= 0.741573:
:...RNA.4 <= 0.1204916:
:...ALT.24 <= 0.2359551: F2 (3.9/1.6)
: ALT.24 > 0.2359551: F4 (4.7)
RNA.4 > 0.1204916:
:...ALT.36 > 0.9213483: F4 (5.1/1.6)
ALT.36 <= 0.9213483:
:...RBC > 0.6041094:
:...ALT.48 > 0.7078652: F3 (17.8/1.6)
: ALT.48 <= 0.7078652:
: :...WBC <= 0.3929748: F1 (7.5/0.8)
: WBC > 0.3929748:
: :...WBC <= 0.7781559: F3 (10.9/3.1)
: WBC > 0.7781559: F1 (4.7/0.8)
RBC <= 0.6041094:
:...ALT.1 <= 0.1123596: F3 (5.9)
ALT.1 > 0.1123596:
:...AST.1 > 0.6853933: F3 (6.2/2.3)
AST.1 <= 0.6853933:
:...ALT.12 > 0.5730337: F3 (3.1/1.6)
ALT.12 <= 0.5730337:
:...ALT.24 <= 0.1460674: F2 (3.1)
ALT.24 > 0.1460674:
:...Age > 0.6896552: F2 (3.1/0.8)
Age <= 0.6896552:
:...WBC <= 0.1912184: F4 (3.1/0.8)
WBC > 0.1912184: F1 (5.5/0.8)
----- Trial 2: -----
Decision tree:
ALT.4 > 0.9213483:
:...RNA.4 > 0.8668897: F3 (5.8/1.9)
: RNA.4 <= 0.8668897:
: :...ALT.24 <= 0.3707865:
: :...WBC > 0.6912184: F1 (5.5/0.6)
: : WBC <= 0.6912184:
: : :...ALT.12 <= 0.4606742: F1 (9.1/1.9)
: : ALT.12 > 0.4606742: F2 (3.8)
: ALT.24 > 0.3707865:
: :...WBC <= 0.5097695:
: :...Plat > 0.8046474: F1 (2.9/0.6)
: : Plat <= 0.8046474:
: : :...Age <= 0.3793103: F1 (5.7/1.4)
: : Age > 0.3793103: F4 (19.3/3.8)
: WBC > 0.5097695:
: :...RBC <= 0.3930546: F3 (3.2/1.3)
: RBC > 0.3930546:
: :...ALT.after.24.w > 0.7391304: F1 (2/0.6)
: ALT.after.24.w <= 0.7391304:
: :...ALT.24 <= 0.8988764: F2 (7.3)
: ALT.24 > 0.8988764: F1 (2)
ALT.4 <= 0.9213483:
:...ALT.after.24.w > 0.8260869:
:...ALT.48 > 0.8764045:
: :...ALT.after.24.w <= 0.8695652: F4 (3.4)
: : ALT.after.24.w > 0.8695652:
: : :...Age > 0.7241379: F2 (10.1/1.3)
: : Age <= 0.7241379:
: : :...BMI <= 0.5384616: F1 (4/0.6)
: : BMI > 0.5384616: F4 (3.3/1.9)
: ALT.48 <= 0.8764045:
: :...RNA.4 > 0.9640629: F3 (7.7/1.3)
: RNA.4 <= 0.9640629:
: :...RNA.4 > 0.5644889:
: :...ALT.1 <= 0.4157303:
: : :...ALT.after.24.w <= 0.9130435:
: : : :...ALT.4 <= 0.8314607: F1 (11/1.9)
: : : : ALT.4 > 0.8314607: F2 (2.6/1.3)
: : : ALT.after.24.w > 0.9130435:
: : : :...ALT.48 <= 0.494382: F1 (5.3/2.6)
: : : ALT.48 > 0.494382: F2 (3.8/1.3)
: : ALT.1 > 0.4157303:
: : :...RNA.4 > 0.9402926: F3 (4.1/1.4)
: : RNA.4 <= 0.9402926:
: : :...AST.1 > 0.8988764: F1 (4.7/1.3)
: : AST.1 <= 0.8988764:
: : :...AST.1 <= 0.2022472: F1 (3.8/1.3)
: : AST.1 > 0.2022472: F4 (22.2/5.2)
: RNA.4 <= 0.5644889:
: :...ALT.4 <= 0.1460674:
: :...RNA.Base <= 0.3900789: F2 (2.6/0.6)
: : RNA.Base > 0.3900789: F4 (7.8/1.3)
: ALT.4 > 0.1460674:
: :...Plat > 0.6354542: F3 (15/3.2)
: Plat <= 0.6354542:
: :...AST.1 > 0.8651685: F3 (5.7/1.4)
: AST.1 <= 0.8651685:
: :...AST.1 > 0.4044944: F1 (19.7/2.5)
: AST.1 <= 0.4044944:
: :...ALT.12 <= 0.5280899:
: :...ALT.4 <= 0.3258427: F2 (2.6/1.3)
: : ALT.4 > 0.3258427: F3 (8.5/2.5)
: ALT.12 > 0.5280899:
: :...Plat <= 0.2032356: F3 (2.6)
: Plat > 0.2032356: F1 (10.3/1.9)
ALT.after.24.w <= 0.8260869:
:...ALT.1 <= 0.1123596:
:...RBC <= 0.03764967: F4 (4.9/0.6)
: RBC > 0.03764967:
: :...BMI <= 0.1538462:
: :...RBC <= 0.4163593: F3 (3.9)
: : RBC > 0.4163593: F4 (5.1/1.3)
: BMI > 0.1538462:
: :...ALT.1 <= 0.02247191:
: :...ALT.48 <= 0.2359551:
: : :...RBC <= 0.6664548: F2 (3.3/0.6)
: : : RBC > 0.6664548: F3 (2.8)
: : ALT.48 > 0.2359551:
: : :...AST.1 <= 0.258427: F1 (2.8)
: : AST.1 > 0.258427: F2 (10.2/2.6)
: ALT.1 > 0.02247191:
: :...AST.1 > 0.9325843: F3 (5.9/1.4)
: AST.1 <= 0.9325843:
: :...ALT.24 <= 0.1123596: F2 (2.5/0.6)
: ALT.24 > 0.1123596:
: :...WBC <= 0.1: F2 (3.9/1.3)
: WBC > 0.1:
: :...AST.1 <= 0.06741573: F1 (4.2/0.6)
: AST.1 > 0.06741573:
: :...ALT.4 > 0.7640449: F3 (9.3/1.4)
: ALT.4 <= 0.7640449:
: :...ALT.1 <= 0.06741573:
: :...ALT.12 <= 0.1910112: F1 (4.7/1.3)
: : ALT.12 > 0.1910112: F3 (11.7/1.9)
: ALT.1 > 0.06741573:
: :...BMI <= 0.5384616: F1 (8.5)
: BMI > 0.5384616:
: :...ALT.4 <= 0.4606742: F1 (4.8/0.6)
: ALT.4 > 0.4606742: F3 (2.6)
ALT.1 > 0.1123596:
:...ALT.after.24.w > 0.6086956:
:...ALT.4 > 0.7865168:
: :...ALT.1 <= 0.7303371: F3 (9.3/1.9)
: : ALT.1 > 0.7303371: F1 (6.1/1.9)
: ALT.4 <= 0.7865168:
: :...RBC > 0.61062:
: :...RNA.4 <= 0.454385:
: : :...WBC <= 0.07091109: F3 (2/0.6)
: : : WBC > 0.07091109: F2 (17.1/2.5)
: : RNA.4 > 0.454385:
: : :...ALT.after.24.w > 0.7826087: F4 (3.3/0.6)
: : ALT.after.24.w <= 0.7826087:
: : :...Plat <= 0.6583615: F3 (19/6.4)
: : Plat > 0.6583615: F2 (6.4/1.9)
: RBC <= 0.61062:
: :...Age > 0.5172414:
: :...ALT.after.24.w > 0.7826087:
: : :...ALT.12 <= 0.5393258: F3 (3.9/0.6)
: : : ALT.12 > 0.5393258: F1 (2.5/1.3)
: : ALT.after.24.w <= 0.7826087:
: : :...ALT.36 > 0.8089887: F4 (5/1.4)
: : ALT.36 <= 0.8089887:
: : :...Age <= 0.7241379:
: : :...AST.1 <= 0.7752809: F1 (5.5/0.6)
: : : AST.1 > 0.7752809: F2 (2.9)
: : Age > 0.7241379:
: : :...ALT.12 <= 0.2022472: F4 (2.5/0.6)
: : ALT.12 > 0.2022472: F2 (9.2)
: Age <= 0.5172414:
: :...ALT.36 <= 0.03370786: F2 (4/0.6)
: ALT.36 > 0.03370786:
: :...ALT.48 > 0.8651685:
: :...RNA.Base <= 0.6867923: F2 (3.9/1.3)
: : RNA.Base > 0.6867923: F4 (2.5/1.3)
: ALT.48 <= 0.8651685:
: :...ALT.12 > 0.3483146: F4 (25.8/3.2)
: ALT.12 <= 0.3483146:
: :...BMI <= 0.4615385: F1 (4/0.6)
: BMI > 0.4615385:
: :...Plat <= 0.7990798: F4 (7.3/1.9)
: Plat > 0.7990798: F1 (2.5/1.3)
ALT.after.24.w <= 0.6086956:
:...RNA.Base > 0.9777441:
:...BMI <= 0.6923077: F1 (6.2/0.6)
: BMI > 0.6923077: F2 (6.5)
RNA.Base <= 0.9777441:
:...ALT.48 <= 0.08988764:
:...WBC > 0.9710209: F2 (3.6)
: WBC <= 0.9710209:
: :...RBC > 0.7907788:
: :...ALT.after.24.w <= 0.4347826: F4 (11.2/1.3)
: : ALT.after.24.w > 0.4347826: F1 (5.7/2)
: RBC <= 0.7907788:
: :...ALT.after.24.w > 0.4347826: F4 (10.4/1.4)
: ALT.after.24.w <= 0.4347826:
: :...RNA.4 <= 0.7591565:
: :...Plat <= 0.07447677: F2 (2.6)
: : Plat > 0.07447677: F3 (10/3.9)
: RNA.4 > 0.7591565:
: :...AST.1 <= 0.494382: F1 (3.2/0.6)
: AST.1 > 0.494382: F2 (3.4)
ALT.48 > 0.08988764:
:...Age > 0.7931035:
:...ALT.after.24.w > 0.5652174:
: :...Plat <= 0.5066878: F3 (3.4)
: : Plat > 0.5066878: F4 (5.7/0.6)
: ALT.after.24.w <= 0.5652174:
: :...BMI <= 0.5384616:
: :...AST.1 > 0.7977528: F3 (9.7/1.3)
: : AST.1 <= 0.7977528:
: : :...ALT.24 <= 0.3033708: F4 (7.9/1.3)
: : ALT.24 > 0.3033708:
: : :...ALT.after.24.w <= 0.173913:
: : :...RNA.4 <= 0.3898644: F3 (6/1.3)
: : : RNA.4 > 0.3898644: F4 (5.1/0.6)
: : ALT.after.24.w > 0.173913:
: : :...Age <= 0.862069:
: : :...RNA.4 <= 0.5140375: F1 (5)
: : : RNA.4 > 0.5140375: F3 (6.2/1.3)
: : Age > 0.862069:
: : :...ALT.1 <= 0.6966292: F1 (7.3/1.9)
: : ALT.1 > 0.6966292: F4 (2.5/0.6)
: BMI > 0.5384616:
: :...RNA.4 <= 0.4341563:
: :...ALT.12 <= 0.494382: F1 (8.5/1.3)
: : ALT.12 > 0.494382: F2 (7.3/1.3)
: RNA.4 > 0.4341563:
: :...RBC > 0.7769297:
: :...RBC <= 0.8945807: F1 (4.8)
: : RBC > 0.8945807: F2 (2)
: RBC <= 0.7769297:
: :...ALT.36 <= 0.2808989: F1 (2.9)
: ALT.36 > 0.2808989:
: :...ALT.36 > 0.8764045: F4 (2.9)
: ALT.36 <= 0.8764045: [S1]
Age <= 0.7931035:
:...ALT.48 > 0.9438202:
:...RBC <= 0.218647: F1 (4/1.3)
: RBC > 0.218647:
: :...RNA.4 <= 0.5562931:
: :...Plat <= 0.2321526: F2 (4.3)
: : Plat > 0.2321526: F4 (11.9/5.2)
: RNA.4 > 0.5562931:
: :...RNA.4 <= 0.7738556: F3 (2.5/0.6)
: RNA.4 > 0.7738556: F4 (4.2/0.6)
ALT.48 <= 0.9438202:
:...Age > 0.4827586:
:...WBC > 0.9082327: F3 (12.5/1.9)
: WBC <= 0.9082327:
: :...RNA.4 <= 0.4655524:
: :...ALT.4 > 0.5168539:
: : :...ALT.24 > 0.5393258: F4 (12.3/1.9)
: : : ALT.24 <= 0.5393258:
: : : :...RBC <= 0.568844: F2 (3.8/1.9)
: : : RBC > 0.568844: F1 (3.3)
: : ALT.4 <= 0.5168539:
: : :...Plat <= 0.2729466:
: : :...BMI <= 0.8461539: F4 (5.2)
: : : BMI > 0.8461539: F3 (2.3)
: : Plat > 0.2729466:
: : :...BMI > 0.6923077: F1 (4.7/2)
: : BMI <= 0.6923077:
: : :...ALT.36 <= 0.6292135: F2 (8.3/3.2)
: : ALT.36 > 0.6292135: F3 (6.9/1.3)
: RNA.4 > 0.4655524:
: :...ALT.12 > 0.7078652: F2 (17.7/5.8)
: ALT.12 <= 0.7078652:
: :...BMI <= 0: F4 (4.9/2)
: BMI > 0:
: :...ALT.4 <= 0.4831461: F3 (16.5/1.3)
: ALT.4 > 0.4831461:
: :...RNA.4 <= 0.7096421: F3 (8.2/2)
: RNA.4 > 0.7096421: F2 (5.9/1.3)
Age <= 0.4827586:
:...ALT.4 <= 0.03370786:
:...RNA.4 <= 0.2248704: F1 (3.5)
: RNA.4 > 0.2248704: F2 (7.4/0.6)
ALT.4 > 0.03370786:
:...AST.1 > 0.9213483:
:...BMI <= 0.6153846: F2 (4.7/0.6)
: BMI > 0.6153846:
: :...RNA.4 <= 0.8584142: F4 (6.2/0.6)
: RNA.4 > 0.8584142: F1 (2/0.6)
AST.1 <= 0.9213483:
:...WBC > 0.9534577:
:...WBC <= 0.9710209: F2 (5.7)
: WBC > 0.9710209: F4 (4.8/1.3)
WBC <= 0.9534577:
:...ALT.1 > 0.8764045:
:...ALT.48 > 0.6516854: F3 (5.3/1.9)
: ALT.48 <= 0.6516854: [S2]
ALT.1 <= 0.8764045:
:...BMI <= 0.3846154:
:...ALT.after.24.w <= 0.04347826: [S3]
: ALT.after.24.w > 0.04347826:
: :...ALT.1 > 0.7191011: [S4]
: ALT.1 <= 0.7191011:
: :...ALT.4 <= 0.2247191: [S5]
: ALT.4 > 0.2247191: [S6]
BMI > 0.3846154:
:...BMI <= 0.4615385: [S7]
BMI > 0.4615385: [S8]
SubTree [S1]
ALT.after.24.w <= 0.4782609: F3 (8.6/0.6)
ALT.after.24.w > 0.4782609: F4 (2)
SubTree [S2]
ALT.after.24.w <= 0.5217391: F1 (14.1/1.9)
ALT.after.24.w > 0.5217391: F2 (2.8/1.4)
SubTree [S3]
RNA.Base <= 0.1106484: F1 (2)
RNA.Base > 0.1106484: F2 (3.9/0.6)
SubTree [S4]
ALT.48 <= 0.5730337: F2 (3.2/1.3)
ALT.48 > 0.5730337: F3 (6.5/0.6)
SubTree [S5]
ALT.4 <= 0.1797753: F4 (5.9/2)
ALT.4 > 0.1797753: F1 (4.7)
SubTree [S6]
RBC <= 0.0630459: F1 (2.9)
RBC > 0.0630459:
:...ALT.1 > 0.4494382: F1 (7.8/2.6)
ALT.1 <= 0.4494382:
:...BMI > 0.3076923: F4 (4.5/1.3)
BMI <= 0.3076923:
:...ALT.24 > 0.8988764: F1 (2/0.6)
ALT.24 <= 0.8988764:
:...ALT.12 <= 0.8202247: F3 (19/2.6)
ALT.12 > 0.8202247: F4 (3.3/0.6)
SubTree [S7]
ALT.1 <= 0.3932584: F2 (4.2/0.6)
ALT.1 > 0.3932584: F4 (6.2/1.3)
SubTree [S8]
ALT.after.24.w <= 0.04347826: F3 (5.9/0.6)
ALT.after.24.w > 0.04347826:
:...ALT.36 <= 0.06741573: F4 (3.9/0.6)
ALT.36 > 0.06741573:
:...ALT.48 <= 0.2022472: F2 (5.5/0.6)
ALT.48 > 0.2022472:
:...ALT.24 > 0.8314607:
:...ALT.48 <= 0.8089887: F3 (10.6/0.6)
: ALT.48 > 0.8089887: F2 (2.3)
ALT.24 <= 0.8314607:
:...RBC > 0.7936847:
:...RNA.4 <= 0.3203851: F1 (4/0.6)
: RNA.4 > 0.3203851: F3 (3.9)
RBC <= 0.7936847:
:...RNA.4 <= 0.1508733:
:...WBC <= 0.2165752: F1 (2.6/0.6)
: WBC > 0.2165752: F3 (5.2/0.6)
RNA.4 > 0.1508733:
:...ALT.after.24.w <= 0.2608696:
:...Plat <= 0.4733648: F2 (3.5)
: Plat > 0.4733648: F4 (4.7)
ALT.after.24.w > 0.2608696:
:...ALT.after.24.w > 0.5217391:
:...ALT.1 <= 0.5842696: F3 (3.8/1.9)
: ALT.1 > 0.5842696: F4 (4.5/0.6)
ALT.after.24.w <= 0.5217391:
:...ALT.12 > 0.752809: F3 (3.9/1.3)
ALT.12 <= 0.752809:
:...ALT.1 <= 0.6404495: F1 (3.2)
ALT.1 > 0.6404495: F2 (4.1)
----- Trial 3: -----
Decision tree:
ALT.12 > 0.8876405:
:...ALT.after.24.w > 0.8260869:
: :...BMI <= 0: F1 (3.4/1)
: : BMI > 0:
: : :...BMI > 0.6923077: F3 (2.1/1)
: : BMI <= 0.6923077:
: : :...BMI <= 0.1538462: F3 (6.1/1.2)
: : BMI > 0.1538462: F4 (8.9/1.5)
: ALT.after.24.w <= 0.8260869:
: :...WBC > 0.8140505:
: :...BMI > 0.8461539: F2 (4.2/0.5)
: : BMI <= 0.8461539:
: : :...ALT.4 <= 0.7078652: F4 (4.5/1)
: : ALT.4 > 0.7078652: F3 (2.3)
: WBC <= 0.8140505:
: :...ALT.36 > 0.4606742:
: :...ALT.12 <= 0.9213483: F1 (13.4/4.2)
: : ALT.12 > 0.9213483:
: : :...Age <= 0.4827586:
: : :...ALT.12 <= 0.9662921: F3 (3.4/1.1)
: : : ALT.12 > 0.9662921: F2 (5.5/1.5)
: : Age > 0.4827586:
: : :...ALT.after.24.w <= 0.3043478: F3 (9.2/2.1)
: : ALT.after.24.w > 0.3043478: F1 (5.2/1)
: ALT.36 <= 0.4606742:
: :...ALT.4 <= 0.07865169: F1 (8.4)
: ALT.4 > 0.07865169:
: :...Age > 0.8965517: F2 (3.9/1.1)
: Age <= 0.8965517:
: :...WBC > 0.7529089: F4 (3.6)
: WBC <= 0.7529089:
: :...ALT.4 <= 0.3033708: F4 (2.8/0.5)
: ALT.4 > 0.3033708: F1 (16.2/3.1)
ALT.12 <= 0.8876405:
:...ALT.4 > 0.9213483:
:...Plat > 0.5567062:
: :...ALT.36 <= 0.741573: F2 (11.7/2.8)
: : ALT.36 > 0.741573:
: : :...ALT.4 <= 0.9775281: F1 (6.3/1)
: : ALT.4 > 0.9775281: F3 (3.4/0.5)
: Plat <= 0.5567062:
: :...ALT.after.24.w <= 0.1304348: F2 (4.9/1.2)
: ALT.after.24.w > 0.1304348:
: :...Age > 0.7931035: F1 (7.7/0.5)
: Age <= 0.7931035:
: :...RNA.4 <= 0.3938995:
: :...ALT.24 <= 0.3370787: F2 (2.3)
: : ALT.24 > 0.3370787: F4 (10.5/1.1)
: RNA.4 > 0.3938995:
: :...ALT.36 > 0.8876405: F4 (2.2)
: ALT.36 <= 0.8876405:
: :...Age <= 0.6551724: F1 (12/3.3)
: Age > 0.6551724: F4 (2.3/0.5)
ALT.4 <= 0.9213483:
:...AST.1 <= 0.07865169:
:...ALT.after.24.w <= 0.6086956:
: :...AST.1 <= 0.01123596:
: : :...ALT.48 <= 0.4606742: F2 (4.5/1.6)
: : : ALT.48 > 0.4606742:
: : : :...ALT.36 <= 0.3932584: F2 (4.1/1.2)
: : : ALT.36 > 0.3932584: F4 (3.4)
: : AST.1 > 0.01123596:
: : :...BMI <= 0.07692308: F4 (4.6/1.8)
: : BMI > 0.07692308:
: : :...ALT.36 > 0.1910112: F3 (25.5/8.3)
: : ALT.36 <= 0.1910112:
: : :...ALT.1 <= 0.6966292: F1 (2.6/1.1)
: : ALT.1 > 0.6966292: F4 (3.9/1)
: ALT.after.24.w > 0.6086956:
: :...ALT.after.24.w > 0.9565217:
: :...RNA.4 <= 0.3898644: F3 (2.8)
: : RNA.4 > 0.3898644: F4 (3.7)
: ALT.after.24.w <= 0.9565217:
: :...RNA.4 <= 0.2566892: F4 (8.9/0.5)
: RNA.4 > 0.2566892:
: :...Age <= 0.2758621: F4 (3.5)
: Age > 0.2758621:
: :...ALT.after.24.w <= 0.7391304: F4 (2.8/0.5)
: ALT.after.24.w > 0.7391304: F1 (5.3)
AST.1 > 0.07865169:
:...ALT.1 <= 0.1123596:
:...ALT.1 <= 0:
: :...ALT.36 > 0.5393258: F2 (4.5)
: : ALT.36 <= 0.5393258:
: : :...ALT.24 <= 0.4382023: F1 (4.3)
: : ALT.24 > 0.4382023: F4 (2.3/0.5)
: ALT.1 > 0:
: :...ALT.after.24.w <= 0.04347826:
: :...ALT.36 <= 0.247191: F4 (2.5)
: : ALT.36 > 0.247191:
: : :...BMI <= 0.8461539: F2 (7.1/1.6)
: : BMI > 0.8461539: F3 (2.2)
: ALT.after.24.w > 0.04347826:
: :...ALT.12 <= 0.03370786: F2 (4/0.5)
: ALT.12 > 0.03370786:
: :...Age <= 0.4827586:
: :...ALT.48 <= 0.6067415: F3 (24.2/7.3)
: : ALT.48 > 0.6067415: F1 (7.7/1.6)
: Age > 0.4827586:
: :...Age <= 0.7241379:
: :...BMI <= 0.4615385: F1 (5.2/1.5)
: : BMI > 0.4615385:
: : :...ALT.36 <= 0.6179775: F2 (3.9/1.1)
: : ALT.36 > 0.6179775: F4 (3.2)
: Age > 0.7241379:
: :...ALT.24 <= 0.2359551: F4 (2.3/1)
: ALT.24 > 0.2359551:
: :...RNA.Base <= 0.7824873: F3 (12.3/2.9)
: RNA.Base > 0.7824873: F1 (3.4/1)
ALT.1 > 0.1123596:
:...RNA.Base <= 0.02612077:
:...WBC <= 0.08364435: F1 (2.2)
: WBC > 0.08364435:
: :...RNA.Base <= 0.008851238: F3 (3.9)
: RNA.Base > 0.008851238:
: :...ALT.24 <= 0.1910112: F3 (2.3)
: ALT.24 > 0.1910112: F2 (15.8/2.8)
RNA.Base > 0.02612077:
:...Plat > 0.9386891:
:...ALT.12 <= 0.3033708:
: :...WBC <= 0.4299671: F3 (4/1)
: : WBC > 0.4299671: F2 (11.1/1)
: ALT.12 > 0.3033708:
: :...AST.1 > 0.9662921: F2 (2.5)
: AST.1 <= 0.9662921:
: :...RBC <= 0.7853205: F4 (13.9/2)
: RBC > 0.7853205: F2 (3.4/1.6)
Plat <= 0.9386891:
:...ALT.48 <= 0.06741573:
:...RBC > 0.7907788:
: :...AST.1 > 0.6179775: F4 (6.4)
: : AST.1 <= 0.6179775:
: : :...ALT.4 <= 0.247191: F4 (2.2)
: : ALT.4 > 0.247191: F1 (7.5/1)
: RBC <= 0.7907788:
: :...AST.1 <= 0.5280899:
: :...Plat <= 0.1595642: F3 (3.4/1)
: : Plat > 0.1595642:
: : :...RNA.4 <= 0.8480108: F4 (13.9/3.1)
: : RNA.4 > 0.8480108: F3 (2.3/1)
: AST.1 > 0.5280899:
: :...Age <= 0.137931: F1 (2.3)
: Age > 0.137931:
: :...RBC <= 0.391696: F4 (4.6/1.5)
: RBC > 0.391696: F2 (6.8/0.5)
ALT.48 > 0.06741573:
:...WBC <= 0.06992316:
:...BMI <= 0: F1 (2.3)
: BMI > 0:
: :...AST.1 > 0.7752809: F3 (7.3/1.5)
: AST.1 <= 0.7752809:
: :...ALT.1 <= 0.4606742:
: :...RBC <= 0.5360187: F4 (2.9/0.5)
: : RBC > 0.5360187: F3 (6)
: ALT.1 > 0.4606742:
: :...Plat > 0.6867015: F3 (4/1.6)
: Plat <= 0.6867015:
: :...Plat > 0.1839102: F2 (13)
: Plat <= 0.1839102:
: :...BMI <= 0.3076923: F2 (3.6)
: BMI > 0.3076923: F4 (2.9)
WBC > 0.06992316:
:...ALT.24 <= 0.1685393:
:...WBC > 0.8902305:
: :...AST.1 <= 0.505618: F2 (5.7/0.5)
: : AST.1 > 0.505618:
: : :...ALT.36 <= 0.4831461: F3 (4.6/1.1)
: : ALT.36 > 0.4831461: F1 (4.3/1.2)
: WBC <= 0.8902305:
: :...Plat <= 0.07994695: F1 (5.5/1.5)
: Plat > 0.07994695:
: :...Age <= 0.1034483:
: :...ALT.after.24.w <= 0.3913043: F4 (5.1/0.5)
: : ALT.after.24.w > 0.3913043: F1 (4.7)
: Age > 0.1034483:
: :...RNA.Base > 0.9477385:
: :...RBC <= 0.2768078: F1 (2.5)
: : RBC > 0.2768078: F4 (3.6)
: RNA.Base <= 0.9477385:
: :...ALT.1 > 0.9213483:
: :...Plat <= 0.5311762: F3 (3.4)
: : Plat > 0.5311762: F2 (3.6/1.1)
: ALT.1 <= 0.9213483:
: :...ALT.12 <= 0.5280899:
: :...BMI <= 0.8461539: F4 (22.7/6)
: : BMI > 0.8461539: F2 (7.2/2.6)
: ALT.12 > 0.5280899:
: :...ALT.4 > 0.4382023: [S1]
: ALT.4 <= 0.4382023: [S2]
ALT.24 > 0.1685393:
:...ALT.after.24.w > 0.9130435:
:...RNA.4 > 0.609365:
: :...ALT.1 <= 0.4494382: F1 (3.2/1.5)
: : ALT.1 > 0.4494382: F4 (7/1.2)
: RNA.4 <= 0.609365:
: :...BMI > 0.6923077: F3 (7.3/0.5)
: BMI <= 0.6923077:
: :...ALT.12 <= 0.1460674: F3 (5.7/1.1)
: ALT.12 > 0.1460674: F1 (12.5/2.3)
ALT.after.24.w <= 0.9130435:
:...ALT.12 > 0.7977528:
:...RBC <= 0.4123253:
: :...ALT.4 <= 0.4494382: F4 (3.8/1.5)
: : ALT.4 > 0.4494382: F1 (3.5/0.5)
: RBC > 0.4123253:
: :...Age <= 0.3103448: F2 (12.5/1.2)
: Age > 0.3103448: [S3]
ALT.12 <= 0.7977528:
:...Age > 0.7241379:
:...ALT.after.24.w > 0.6521739:
: :...ALT.24 <= 0.3033708: F3 (2.9)
: : ALT.24 > 0.3033708:
: : :...ALT.1 <= 0.3370787: F1 (2.3/0.5)
: : ALT.1 > 0.3370787: F2 (21.4/3.8)
: ALT.after.24.w <= 0.6521739:
: :...ALT.12 <= 0.03370786: F4 (2.9)
: ALT.12 > 0.03370786:
: :...ALT.1 <= 0.3595506: [S4]
: ALT.1 > 0.3595506:
: :...ALT.4 > 0.8089887: [S5]
: ALT.4 <= 0.8089887: [S6]
Age <= 0.7241379:
:...ALT.1 > 0.8539326:
:...ALT.4 <= 0.03370786: F3 (3.6)
: ALT.4 > 0.03370786:
: :...Plat <= 0.2402005: [S7]
: Plat > 0.2402005:
: :...RBC > 0.803508: F2 (3.5/1.2)
: RBC <= 0.803508:
: :...Age <= 0.06896552: [S8]
: Age > 0.06896552: [S9]
ALT.1 <= 0.8539326:
:...ALT.12 > 0.4157303:
:...ALT.48 > 0.9438202: F4 (5.8)
: ALT.48 <= 0.9438202:
: :...ALT.1 > 0.5730337:
: :...Plat <= 0.3866588: [S10]
: : Plat > 0.3866588: [S11]
: ALT.1 <= 0.5730337: [S12]
ALT.12 <= 0.4157303:
:...RNA.Base <= 0.1034706: [S13]
RNA.Base > 0.1034706:
:...ALT.48 > 0.8202247: [S14]
ALT.48 <= 0.8202247:
:...RBC > 0.9123615: [S15]
RBC <= 0.9123615: [S16]
SubTree [S1]
ALT.4 <= 0.8202247: F4 (8.9/1)
ALT.4 > 0.8202247: F2 (2.1/1)
SubTree [S2]
ALT.24 > 0.05617978: F3 (7)
ALT.24 <= 0.05617978:
:...ALT.12 <= 0.741573: F4 (4.6/0.5)
ALT.12 > 0.741573: F3 (4.9/1.2)
SubTree [S3]
ALT.after.24.w <= 0.173913: F2 (4.4/0.5)
ALT.after.24.w > 0.173913:
:...ALT.4 <= 0.3146068: F4 (2.9)
ALT.4 > 0.3146068: F3 (8.8/2.6)
SubTree [S4]
ALT.after.24.w > 0.4782609: F1 (6.3/1.6)
ALT.after.24.w <= 0.4782609:
:...ALT.4 <= 0.3370787: F1 (4.7/1.6)
ALT.4 > 0.3370787: F2 (10.1/0.5)
SubTree [S5]
ALT.12 <= 0.3932584: F3 (4.5/1.7)
ALT.12 > 0.3932584: F4 (5.7/1.1)
SubTree [S6]
Plat > 0.7286869: F4 (2.8)
Plat <= 0.7286869:
:...Plat <= 0.01514413: F3 (2.7/1.1)
Plat > 0.01514413:
:...ALT.36 <= 0.3370787: F1 (9.2/1.1)
ALT.36 > 0.3370787:
:...ALT.4 <= 0.5617977: F3 (5.7/2.1)
ALT.4 > 0.5617977: F1 (6.5/0.5)
SubTree [S7]
ALT.1 <= 0.9662921: F2 (6.4/1.8)
ALT.1 > 0.9662921: F4 (3.2)
SubTree [S8]
ALT.1 <= 0.9438202: F1 (2.1)
ALT.1 > 0.9438202: F3 (4/1.2)
SubTree [S9]
BMI > 0.3846154: F1 (15.6/1)
BMI <= 0.3846154:
:...ALT.36 <= 0.8988764: F4 (4/0.5)
ALT.36 > 0.8988764: F1 (2.1)
SubTree [S10]
WBC <= 0.3199781: F2 (2)
WBC > 0.3199781:
:...ALT.12 <= 0.5730337: F4 (5.5/1.6)
ALT.12 > 0.5730337: F3 (5.9/0.5)
SubTree [S11]
ALT.4 > 0.6966292: F2 (5.2/0.5)
ALT.4 <= 0.6966292:
:...ALT.24 <= 0.5393258: F2 (3.7/0.5)
ALT.24 > 0.5393258: F3 (7.8/1.6)
SubTree [S12]
RNA.4 <= 0.3030731: F4 (16.3/2.3)
RNA.4 > 0.3030731:
:...ALT.48 <= 0.4719101:
:...BMI <= 0.3846154: F1 (5.2/2.3)
: BMI > 0.3846154:
: :...RNA.Base <= 0.7122203: F4 (9.7/0.5)
: RNA.Base > 0.7122203: F2 (3.6)
ALT.48 > 0.4719101:
:...BMI <= 0.3076923:
:...AST.1 <= 0.4157303: F2 (2.3)
: AST.1 > 0.4157303: F3 (4.1/0.5)
BMI > 0.3076923:
:...Plat <= 0.6304561: F1 (9.2/1)
Plat > 0.6304561: F3 (2.9/0.5)
SubTree [S13]
RNA.Base <= 0.0443486: F4 (4.2/1.7)
RNA.Base > 0.0443486: F1 (8.2/1)
SubTree [S14]
ALT.1 <= 0.5280899: F2 (6.9/1)
ALT.1 > 0.5280899: F3 (8.2/1.7)
SubTree [S15]
AST.1 <= 0.6067415: F4 (4.8)
AST.1 > 0.6067415: F3 (3.4/1.1)
SubTree [S16]
ALT.12 > 0.3707865: F3 (8.2/1.6)
ALT.12 <= 0.3707865:
:...ALT.12 <= 0.1348315: F3 (16.9/5.5)
ALT.12 > 0.1348315:
:...RNA.4 > 0.7930099:
:...RNA.Base <= 0.4821797: F3 (2.1)
: RNA.Base > 0.4821797: F4 (4/1.2)
RNA.4 <= 0.7930099:
:...WBC <= 0.5304061:
:...ALT.36 <= 0.5842696: F3 (5.1/1.1)
: ALT.36 > 0.5842696: F1 (6.7/2)
WBC > 0.5304061:
:...RNA.Base > 0.6795371: F1 (4.7)
RNA.Base <= 0.6795371:
:...RNA.4 <= 0.1410989: F4 (2.8/1.2)
RNA.4 > 0.1410989:
:...RBC <= 0.2451413: F2 (2.7)
RBC > 0.2451413: F1 (4.9/1)
----- Trial 4: -----
Decision tree:
BMI > 0.4615385:
:...WBC <= 0.04643249:
: :...ALT.4 <= 0.2134831: F2 (4)
: : ALT.4 > 0.2134831:
: : :...ALT.48 > 0.752809: F3 (3.7/1.1)
: : ALT.48 <= 0.752809:
: : :...RNA.Base <= 0.1958179: F1 (6.1)
: : RNA.Base > 0.1958179:
: : :...ALT.after.24.w <= 0.3913043: F1 (4/1)
: : ALT.after.24.w > 0.3913043: F3 (5/0.4)
: WBC > 0.04643249:
: :...ALT.after.24.w > 0.5217391:
: :...AST.1 <= 0.1348315:
: : :...ALT.after.24.w > 0.8695652: F1 (6.8/1.8)
: : : ALT.after.24.w <= 0.8695652:
: : : :...ALT.12 > 0.8426966: F1 (3.4/0.9)
: : : ALT.12 <= 0.8426966:
: : : :...AST.1 <= 0.06741573: F4 (5.6)
: : : AST.1 > 0.06741573: F3 (4.3/1.4)
: : AST.1 > 0.1348315:
: : :...ALT.12 > 0.3932584:
: : :...BMI > 0.9230769: F2 (7.8/4.2)
: : : BMI <= 0.9230769:
: : : :...AST.1 > 0.741573:
: : : :...RNA.4 > 0.7758369: F1 (4.1/1.4)
: : : : RNA.4 <= 0.7758369:
: : : : :...ALT.4 <= 0.5617977: F4 (13.7)
: : : : ALT.4 > 0.5617977:
: : : : :...ALT.1 <= 0.3820225: F1 (2.8)
: : : : ALT.1 > 0.3820225: F4 (7.4/2.9)
: : : AST.1 <= 0.741573:
: : : :...RBC > 0.9025032: F2 (6.5/1)
: : : RBC <= 0.9025032:
: : : :...ALT.4 <= 0.06741573: F3 (4/1.4)
: : : ALT.4 > 0.06741573:
: : : :...Age > 0.8275862: F2 (5.9/1.1)
: : : Age <= 0.8275862:
: : : :...ALT.1 <= 0.1573034: F2 (5.2/2.4)
: : : ALT.1 > 0.1573034:
: : : :...RNA.4 > 0.8100964: F4 (11.7/1)
: : : RNA.4 <= 0.8100964:
: : : :...Age <= 0.1724138: F2 (5/1.9)
: : : Age > 0.1724138:
: : : :...RNA.4 <= 0.7061995: F4 (13.6/2.5)
: : : RNA.4 > 0.7061995: F2 (5.6/1.3)
: : ALT.12 <= 0.3932584:
: : :...ALT.12 > 0.3707865:
: : :...RNA.4 <= 0.2267619: F1 (3.4)
: : : RNA.4 > 0.2267619: F3 (5)
: : ALT.12 <= 0.3707865:
: : :...ALT.after.24.w <= 0.5652174: F4 (4.9/2)
: : ALT.after.24.w > 0.5652174:
: : :...ALT.24 > 0.8651685:
: : :...AST.1 <= 0.6292135: F3 (4.6/1)
: : : AST.1 > 0.6292135: F2 (6/0.4)
: : ALT.24 <= 0.8651685:
: : :...Age > 0.7586207:
: : :...Age <= 0.8965517: F2 (11.2/2.3)
: : : Age > 0.8965517: F4 (3)
: : Age <= 0.7586207:
: : :...ALT.4 > 0.7977528:
: : :...RNA.4 > 0.8333284: F3 (3.8)
: : : RNA.4 <= 0.8333284:
: : : :...ALT.1 <= 0.3258427: F3 (2.5/0.4)
: : : ALT.1 > 0.3258427: F1 (7.4/1)
: : ALT.4 <= 0.7977528:
: : :...ALT.12 > 0.2808989: F2 (4.8/0.4)
: : ALT.12 <= 0.2808989:
: : :...ALT.4 <= 0.2808989:
: : :...RBC <= 0.564325: F1 (9.5/3.2)
: : : RBC > 0.564325: F3 (2.3/0.4)
: : ALT.4 > 0.2808989:
: : :...RNA.Base > 0.5666882:
: : :...RBC <= 0.5659373: F3 (6.5/1.1)
: : : RBC > 0.5659373: F4 (2.4)
: : RNA.Base <= 0.5666882:
: : :...Plat <= 0.2321526: F1 (2.4/0.9)
: : Plat > 0.2321526:
: : :...ALT.36 <= 0.7303371: F2 (5.8/0.4)
: : ALT.36 > 0.7303371: F4 (2.6)
: ALT.after.24.w <= 0.5217391:
: :...ALT.after.24.w > 0.4347826:
: :...ALT.12 <= 0.04494382: F2 (5.6/0.4)
: : ALT.12 > 0.04494382:
: : :...ALT.24 <= 0.2359551:
: : :...ALT.1 <= 0.7865168: F1 (2.8/0.4)
: : : ALT.1 > 0.7865168: F4 (4.4)
: : ALT.24 > 0.2359551:
: : :...ALT.after.24.w <= 0.4782609:
: : :...AST.1 <= 0.1123596: F3 (2.6)
: : : AST.1 > 0.1123596: F1 (11.1/2.5)
: : ALT.after.24.w > 0.4782609:
: : :...RBC <= 0.3063387: F1 (4.1)
: : RBC > 0.3063387:
: : :...WBC <= 0.1418222: F3 (2.6)
: : WBC > 0.1418222:
: : :...RBC <= 0.7555608: F2 (4.7)
: : RBC > 0.7555608: F1 (2.3/0.8)
: ALT.after.24.w <= 0.4347826:
: :...ALT.48 > 0.8426966:
: :...Age <= 0.137931: F2 (4.7/1.1)
: : Age > 0.137931:
: : :...BMI > 0.7692308:
: : :...Age > 0.7241379: F1 (2.5)
: : : Age <= 0.7241379:
: : : :...ALT.4 <= 0.4494382: F1 (3.9/1.1)
: : : ALT.4 > 0.4494382: F4 (7.6)
: : BMI <= 0.7692308:
: : :...BMI <= 0.5384616: F2 (2.5)
: : BMI > 0.5384616:
: : :...Plat > 0.7601966: F4 (2.6/1.1)
: : Plat <= 0.7601966:
: : :...Age <= 0.7931035: F3 (6.3/2.4)
: : Age > 0.7931035: F1 (4.7/0.4)
: ALT.48 <= 0.8426966:
: :...WBC <= 0.09363337: F2 (6.5/0.9)
: WBC > 0.09363337:
: :...ALT.12 <= 0.1797753:
: :...ALT.4 <= 0.3595506:
: : :...WBC <= 0.4979144: F1 (10/2.2)
: : : WBC > 0.4979144: F3 (3.6)
: : ALT.4 > 0.3595506:
: : :...ALT.1 <= 0.3820225: F4 (6.1/0.4)
: : ALT.1 > 0.3820225:
: : :...RNA.4 <= 0.2295246: F4 (3/0.4)
: : RNA.4 > 0.2295246:
: : :...ALT.12 <= 0.1123596: F2 (6.4)
: : ALT.12 > 0.1123596: F1 (2.2)
: ALT.12 > 0.1797753:
: :...ALT.48 > 0.8202247: F2 (4.8)
: ALT.48 <= 0.8202247:
: :...ALT.4 <= 0.05617978:
: :...ALT.after.24.w <= 0.3478261: F1 (8.3/1.6)
: : ALT.after.24.w > 0.3478261: F3 (5.7/2.2)
: ALT.4 > 0.05617978:
: :...Plat > 0.9282733:
: :...ALT.24 <= 0.741573: F2 (3.7)
: : ALT.24 > 0.741573: F4 (2.9)
: Plat <= 0.9282733:
: :...ALT.12 > 0.7977528:
: :...BMI > 0.9230769: F1 (2.3/0.9)
: : BMI <= 0.9230769:
: : :...RNA.Base <= 0.542564: F3 (15.1/1.8)
: : RNA.Base > 0.542564: F2 (9.9/1.6)
: ALT.12 <= 0.7977528:
: :...ALT.48 > 0.5842696:
: :...RNA.Base > 0.7295456: F4 (6.2/1.8)
: : RNA.Base <= 0.7295456:
: : :...Plat <= 0.2682108: F4 (3.4)
: : Plat > 0.2682108: F3 (9.2/2.7)
: ALT.48 <= 0.5842696:
: :...ALT.4 <= 0.6853933:
: :...ALT.after.24.w > 0.08695652:
: : :...AST.1 <= 0.1011236: F2 (5.3/2.3)
: : : AST.1 > 0.1011236: F3 (20.6/4.9)
: : ALT.after.24.w <= 0.08695652:
: : :...ALT.1 <= 0.2022472: F2 (4.1/1.9)
: : ALT.1 > 0.2022472:
: : :...Age <= 0.2758621: F4 (3.2/1.3)
: : Age > 0.2758621: F3 (4)
: ALT.4 > 0.6853933:
: :...ALT.48 > 0.4382023: F3 (5.6/0.8)
: ALT.48 <= 0.4382023:
: :...BMI <= 0.6923077: F2 (3.9/1.4)
: BMI > 0.6923077:
: :...WBC <= 0.2931943: F1 (3.4/0.4)
: WBC > 0.2931943: [S1]
BMI <= 0.4615385:
:...AST.1 > 0.6966292:
:...ALT.1 <= 0.05617978:
: :...RBC <= 0.6272686: F3 (4.3/0.4)
: : RBC > 0.6272686: F1 (5)
: ALT.1 > 0.05617978:
: :...RNA.4 <= 0.1096454:
: :...RBC <= 0.1361606: F3 (3.7/0.4)
: : RBC > 0.1361606:
: : :...Plat <= 0.6185191: F4 (11.8/1.9)
: : Plat > 0.6185191: F2 (3.1)
: RNA.4 > 0.1096454:
: :...ALT.48 > 0.9438202: F2 (5.8)
: ALT.48 <= 0.9438202:
: :...RNA.4 <= 0.1684916: F1 (3.3)
: RNA.4 > 0.1684916:
: :...BMI > 0.3846154:
: :...WBC > 0.3660812: F3 (8.8/2.4)
: : WBC <= 0.3660812:
: : :...RNA.Base <= 0.3681011: F4 (2.5)
: : RNA.Base > 0.3681011: F1 (4/0.4)
: BMI <= 0.3846154:
: :...RNA.4 > 0.8480108:
: :...ALT.48 <= 0.1011236: F2 (3.8/1.9)
: : ALT.48 > 0.1011236:
: : :...BMI > 0.3076923: F1 (2.9/0.9)
: : BMI <= 0.3076923:
: : :...BMI <= 0.07692308: F1 (5.4/0.9)
: : BMI > 0.07692308: F3 (4.7)
: RNA.4 <= 0.8480108:
: :...Age > 0.4482759:
: :...AST.1 <= 0.7303371: F4 (3.5/1.1)
: : AST.1 > 0.7303371:
: : :...BMI > 0.1538462:
: : :...ALT.12 <= 0.5955056: F2 (11/1.3)
: : : ALT.12 > 0.5955056: F3 (3.1/0.4)
: : BMI <= 0.1538462:
: : :...ALT.4 > 0.505618: F3 (7.6)
: : ALT.4 <= 0.505618:
: : :...ALT.4 <= 0.1797753: F3 (5.6/0.9)
: : ALT.4 > 0.1797753: F2 (4.2)
: Age <= 0.4482759:
: :...RNA.Base <= 0.1106484: F1 (2.2)
: RNA.Base > 0.1106484:
: :...BMI > 0.3076923:
: :...ALT.after.24.w <= 0.5652174: F1 (3.1/1)
: : ALT.after.24.w > 0.5652174: F2 (2.8)
: BMI <= 0.3076923:
: :...BMI <= 0.07692308:
: :...ALT.1 <= 0.4831461: F4 (4.4/0.8)
: : ALT.1 > 0.4831461: F2 (3.8)
: BMI > 0.07692308:
: :...AST.1 > 0.9325843: F4 (2.5)
: AST.1 <= 0.9325843:
: :...WBC <= 0.1086718: F4 (3.2/1)
: WBC > 0.1086718:
: :...ALT.1 <= 0.1460674: F2 (2.6)
: ALT.1 > 0.1460674: F3 (9.6/1.3)
AST.1 <= 0.6966292:
:...AST.1 > 0.6179775:
:...ALT.12 <= 0.3707865:
: :...RBC <= 0.4879217: F1 (5/1)
: : RBC > 0.4879217: F2 (5.6/2.7)
: ALT.12 > 0.3707865:
: :...RNA.Base <= 0.123665: F3 (2.5/0.4)
: RNA.Base > 0.123665:
: :...WBC <= 0.1587267: F4 (4.2)
: WBC > 0.1587267:
: :...ALT.48 <= 0.1123596: F4 (2.5)
: ALT.48 > 0.1123596: F1 (21.6/4)
AST.1 <= 0.6179775:
:...RNA.Base > 0.6363708:
:...ALT.12 <= 0.03370786: F3 (4)
: ALT.12 > 0.03370786:
: :...ALT.24 > 0.8426966:
: :...AST.1 <= 0.2921348: F4 (6.6/2.7)
: : AST.1 > 0.2921348: F1 (8.2)
: ALT.24 <= 0.8426966:
: :...ALT.12 <= 0.4269663:
: :...ALT.after.24.w > 0.9565217: F3 (2.1/1)
: : ALT.after.24.w <= 0.9565217:
: : :...ALT.48 > 0.8314607: F4 (5.3/2)
: : ALT.48 <= 0.8314607:
: : :...Plat <= 0.2797206: F1 (5.8/1.4)
: : Plat > 0.2797206:
: : :...WBC <= 0.7645444: F4 (11.7/1.9)
: : WBC > 0.7645444: F1 (4.4/0.4)
: ALT.12 > 0.4269663:
: :...Plat > 0.9565158: F1 (5)
: Plat <= 0.9565158:
: :...AST.1 > 0.5617977:
: :...ALT.24 <= 0.3707865: F3 (3.9/1)
: : ALT.24 > 0.3707865: F2 (3.4/1)
: AST.1 <= 0.5617977:
: :...ALT.36 > 0.7977528: F3 (10.2/1.8)
: ALT.36 <= 0.7977528:
: :...ALT.12 <= 0.6516854:
: :...ALT.24 <= 0.08988764: F3 (2.6)
: : ALT.24 > 0.08988764: F4 (14.4/3.1)
: ALT.12 > 0.6516854:
: :...ALT.12 <= 0.7078652: F3 (2.9)
: ALT.12 > 0.7078652:
: :...WBC <= 0.2755214: F1 (4.7)
: WBC > 0.2755214:
: :...Plat <= 0.2797206: F3 (3.7)
: Plat > 0.2797206:
: :...ALT.4 <= 0.4269663: F1 (3.7/0.9)
: ALT.4 > 0.4269663: F4 (4.3/1.1)
RNA.Base <= 0.6363708:
:...Age <= 0.1724138:
:...Age <= 0.03448276:
: :...ALT.36 <= 0.3595506: F2 (4.6/1.1)
: : ALT.36 > 0.3595506: F4 (7.1/2.8)
: Age > 0.03448276:
: :...ALT.after.24.w > 0.4347826: F1 (15.1/3.4)
: ALT.after.24.w <= 0.4347826:
: :...ALT.4 <= 0.6404495: F4 (10.1/2.3)
: ALT.4 > 0.6404495: F3 (2.7)
Age > 0.1724138:
:...RNA.Base <= 0.02975085:
:...ALT.1 > 0.6741573: F2 (2.4/0.4)
: ALT.1 <= 0.6741573:
: :...RNA.4 <= 0.2949855: F3 (2.4)
: RNA.4 > 0.2949855: F1 (7.3/1)
RNA.Base > 0.02975085:
:...ALT.after.24.w <= 0.08695652:
:...WBC > 0.859056: F3 (2.5/0.4)
: WBC <= 0.859056:
: :...Age <= 0.6206896: F2 (13.9/2.5)
: Age > 0.6206896: F4 (7.5/1.6)
ALT.after.24.w > 0.08695652:
:...WBC > 0.874314: F4 (10.7/2.3)
WBC <= 0.874314:
:...RNA.4 > 0.9036831:
:...ALT.48 <= 0.4831461: F3 (10.9/1.4)
: ALT.48 > 0.4831461: F1 (3.4/0.4)
RNA.4 <= 0.9036831:
:...Age <= 0.2413793:
:...RNA.4 <= 0.1096454: F3 (2.3/0.4)
: RNA.4 > 0.1096454: F4 (6.3/0.8)
Age > 0.2413793:
:...Age <= 0.3103448:
:...RNA.Base <= 0.3949795: F2 (6.1)
: RNA.Base > 0.3949795: F3 (2.1)
Age > 0.3103448:
:...RNA.4 <= 0.08631617: F4 (8.6/1.3)
RNA.4 > 0.08631617:
:...Age <= 0.3793103:
:...ALT.48 <= 0.7752809: F3 (10.6/3)
: ALT.48 > 0.7752809: F1 (3.8/1)
Age > 0.3793103:
:...ALT.48 > 0.8764045:
:...ALT.48 <= 0.9662921: F2 (11.4/1.1)
: ALT.48 > 0.9662921: F3 (3.7/1.9)
ALT.48 <= 0.8764045:
:...AST.1 > 0.5168539:
:...WBC <= 0.4299671: F4 (3)
: WBC > 0.4299671: F2 (6.7/0.9)
AST.1 <= 0.5168539:
:...ALT.24 > 0.7977528: [S2]
ALT.24 <= 0.7977528: [S3]
SubTree [S1]
RBC <= 0.8784513: F2 (7.1)
RBC > 0.8784513: F1 (2.6)
SubTree [S2]
Plat <= 0.08592667: F1 (2.5/1.1)
Plat > 0.08592667:
:...ALT.4 <= 0.7977528: F3 (4.5)
ALT.4 > 0.7977528: F4 (2.1)
SubTree [S3]
RBC <= 0.05493545: F2 (3.9/1.1)
RBC > 0.05493545:
:...AST.1 > 0.3146068:
:...ALT.12 <= 0.6741573: F2 (4.5/0.8)
: ALT.12 > 0.6741573: F1 (6.8)
AST.1 <= 0.3146068:
:...RNA.Base <= 0.04202569: F2 (2.3/1.1)
RNA.Base > 0.04202569:
:...RNA.4 <= 0.2989016: F4 (4.7/0.8)
RNA.4 > 0.2989016:
:...ALT.12 <= 0.7640449: F1 (13.4/2.9)
ALT.12 > 0.7640449: F4 (2.9)
----- Trial 5: -----
Decision tree:
ALT.1 <= 0.1235955:
:...Plat > 0.8046474:
: :...ALT.36 <= 0.2808989: F1 (4.8/0.9)
: : ALT.36 > 0.2808989:
: : :...WBC <= 0.4256861: F3 (9.3/1.5)
: : WBC > 0.4256861: F2 (9.6/2)
: Plat <= 0.8046474:
: :...WBC <= 0.2394072:
: :...RBC <= 0.427889: F2 (7.6/1.2)
: : RBC > 0.427889:
: : :...ALT.48 <= 0.2359551: F3 (3.2/0.7)
: : ALT.48 > 0.2359551:
: : :...Plat <= 0.542229: F1 (11.3/0.7)
: : Plat > 0.542229: F2 (3.3/0.8)
: WBC > 0.2394072:
: :...ALT.12 <= 0.03370786:
: :...RBC <= 0.4599498: F2 (4.1)
: : RBC > 0.4599498: F4 (2.8/0.9)
: ALT.12 > 0.03370786:
: :...ALT.1 <= 0:
: :...ALT.12 <= 0.4719101: F2 (3.9/1.3)
: : ALT.12 > 0.4719101: F4 (2.7)
: ALT.1 > 0:
: :...Age <= 0.03448276: F1 (4.4)
: Age > 0.03448276:
: :...ALT.1 <= 0.03370786:
: :...RNA.Base > 0.5666882: F4 (5.7/0.3)
: : RNA.Base <= 0.5666882:
: : :...ALT.24 <= 0.4269663: F4 (3.4/0.8)
: : ALT.24 > 0.4269663: F3 (9.1/1.4)
: ALT.1 > 0.03370786:
: :...ALT.after.24.w <= 0.3913043:
: :...ALT.after.24.w <= 0.04347826: F3 (3.4/1.3)
: : ALT.after.24.w > 0.04347826:
: : :...BMI <= 0.6923077: F1 (8.5/1.5)
: : BMI > 0.6923077: F3 (9.4/2.9)
: ALT.after.24.w > 0.3913043:
: :...ALT.1 > 0.1123596: F2 (4.1/1.7)
: ALT.1 <= 0.1123596:
: :...Age <= 0.6896552:
: :...Age <= 0.4827586: F3 (6.4/1.5)
: : Age > 0.4827586: F4 (5.3)
: Age > 0.6896552:
: :...Plat <= 0.2512533: F3 (3.5/1.2)
: Plat > 0.2512533: F1 (4.2/0.3)
ALT.1 > 0.1235955:
:...WBC <= 0.02327113:
:...Plat > 0.861215: F1 (5.3/1.7)
: Plat <= 0.861215:
: :...RNA.Base > 0.7096235: F2 (5.8)
: RNA.Base <= 0.7096235:
: :...Plat <= 0.5482687: F3 (5.5)
: Plat > 0.5482687: F2 (4.7/1.6)
WBC > 0.02327113:
:...Age > 0.8275862:
:...RBC > 0.9401246:
: :...Plat <= 0.5906887: F3 (6)
: : Plat > 0.5906887: F2 (2.8)
: RBC <= 0.9401246:
: :...RNA.4 <= 0.4928535:
: :...Age <= 0.862069:
: : :...WBC <= 0.3787047: F3 (4)
: : : WBC > 0.3787047: F2 (8.7/1.5)
: : Age > 0.862069:
: : :...AST.1 <= 0.06741573: F4 (4.8/0.9)
: : AST.1 > 0.06741573:
: : :...RBC <= 0.1844323:
: : :...ALT.12 <= 0.2808989: F3 (3.9/1.5)
: : : ALT.12 > 0.2808989: F2 (9.1)
: : RBC > 0.1844323:
: : :...AST.1 > 0.8089887: F3 (4.7/1.2)
: : AST.1 <= 0.8089887:
: : :...BMI > 0.5384616:
: : :...RBC <= 0.342911: F1 (4.9/0.8)
: : : RBC > 0.342911: F2 (7/1.7)
: : BMI <= 0.5384616:
: : :...ALT.4 > 0.7191011: F1 (5.9)
: : ALT.4 <= 0.7191011:
: : :...ALT.36 <= 0.6179775: F1 (8.9/2.8)
: : ALT.36 > 0.6179775: F4 (4.8/2)
: RNA.4 > 0.4928535:
: :...ALT.12 <= 0.1797753: F4 (6.1/1)
: ALT.12 > 0.1797753:
: :...ALT.36 > 0.8426966:
: :...RNA.4 <= 0.8260288: F4 (4.9)
: : RNA.4 > 0.8260288: F3 (4.9/2.1)
: ALT.36 <= 0.8426966:
: :...Age > 0.9655172: F4 (5.1/2.5)
: Age <= 0.9655172:
: :...RNA.4 <= 0.7080036:
: :...BMI <= 0.1538462: F1 (2.8)
: : BMI > 0.1538462:
: : :...ALT.after.24.w <= 0.8695652: F3 (10.9/1.1)
: : ALT.after.24.w > 0.8695652: F1 (3.5/0.9)
: RNA.4 > 0.7080036:
: :...AST.1 <= 0.1797753: F1 (5.8)
: AST.1 > 0.1797753:
: :...RNA.4 <= 0.8188623:
: :...RNA.Base <= 0.5865454: F2 (3.4/0.3)
: : RNA.Base > 0.5865454: F4 (2.4)
: RNA.4 > 0.8188623:
: :...ALT.1 <= 0.5955056: F1 (5/1)
: ALT.1 > 0.5955056: F3 (5.6/1.4)
Age <= 0.8275862:
:...RNA.Base > 0.9228824:
:...BMI > 0.3846154:
: :...AST.1 <= 0.3033708: F3 (8.4/2)
: : AST.1 > 0.3033708:
: : :...ALT.12 <= 0.3258427: F1 (9.2/3.2)
: : ALT.12 > 0.3258427:
: : :...ALT.12 <= 0.8202247: F2 (7.2/0.8)
: : ALT.12 > 0.8202247: F4 (3.4/1.1)
: BMI <= 0.3846154:
: :...AST.1 > 0.7191011: F3 (3.6)
: AST.1 <= 0.7191011:
: :...ALT.1 <= 0.4606742: F1 (8.1)
: ALT.1 > 0.4606742:
: :...ALT.1 <= 0.7191011: F3 (6.9/2.3)
: ALT.1 > 0.7191011:
: :...RBC <= 0.7577587: F1 (5.7/0.3)
: RBC > 0.7577587: F4 (2.4)
RNA.Base <= 0.9228824:
:...ALT.48 > 0.9438202:
:...ALT.1 > 0.8651685: F1 (4.5/2.3)
: ALT.1 <= 0.8651685:
: :...ALT.4 <= 0.1235955: F3 (4.5/1.9)
: ALT.4 > 0.1235955:
: :...BMI <= 0.2307692: F2 (8.6/2.4)
: BMI > 0.2307692:
: :...ALT.12 <= 0.06741573: F2 (2.8)
: ALT.12 > 0.06741573: F4 (17.6/3.1)
ALT.48 <= 0.9438202:
:...WBC <= 0.06355653:
:...RBC > 0.6630681: F1 (5.9/1.6)
: RBC <= 0.6630681:
: :...ALT.after.24.w <= 0.3913043: F3 (3.5/0.9)
: ALT.after.24.w > 0.3913043:
: :...ALT.24 <= 0.4719101: F4 (6.7)
: ALT.24 > 0.4719101:
: :...RNA.Base <= 0.5038445: F3 (4.2)
: RNA.Base > 0.5038445: F4 (2.4)
WBC > 0.06355653:
:...ALT.36 <= 0.1685393:
:...ALT.12 > 0.8876405:
: :...ALT.48 > 0.6179775: F2 (3/1.2)
: : ALT.48 <= 0.6179775:
: : :...ALT.after.24.w <= 0.6521739: F1 (5.3)
: : ALT.after.24.w > 0.6521739: F4 (2.9/0.8)
: ALT.12 <= 0.8876405:
: :...RNA.4 <= 0.3265264:
: :...ALT.4 > 0.8876405: F2 (2.2)
: : ALT.4 <= 0.8876405:
: : :...WBC <= 0.3660812: F3 (5.2)
: : WBC > 0.3660812:
: : :...RBC <= 0.1144723: F1 (3.8/0.9)
: : RBC > 0.1144723:
: : :...Age > 0.4482759: F4 (7.8/0.3)
: : Age <= 0.4482759:
: : :...Age <= 0.2068966: F4 (3.3/0.7)
: : Age > 0.2068966: F3 (3.3/0.3)
: RNA.4 > 0.3265264:
: :...ALT.after.24.w > 0.9565217: F4 (3.8/0.7)
: ALT.after.24.w <= 0.9565217:
: :...Age > 0.6206896:
: :...BMI <= 0.4615385: F2 (7.2/1.7)
: : BMI > 0.4615385: F3 (5.4)
: Age <= 0.6206896:
: :...RNA.4 <= 0.5406513: F2 (12.1)
: RNA.4 > 0.5406513:
: :...RBC <= 0.415267:
: :...BMI > 0.5384616: F2 (6.8/2.7)
: : BMI <= 0.5384616:
: : :...RNA.4 <= 0.8075259: F3 (4)
: : RNA.4 > 0.8075259: F1 (2.4/0.8)
: RBC > 0.415267:
: :...ALT.12 > 0.5393258: F2 (3.9)
: ALT.12 <= 0.5393258:
: :...ALT.24 > 0.494382: F4 (6)
: ALT.24 <= 0.494382:
: :...Plat <= 0.5191718: F4 (2.1)
: Plat > 0.5191718: F2 (4.7)
ALT.36 > 0.1685393:
:...RNA.4 <= 0.02513668:
:...ALT.24 > 0.6179775: F1 (7.2)
: ALT.24 <= 0.6179775:
: :...ALT.12 <= 0.4494382: F2 (2.5/0.7)
: ALT.12 > 0.4494382: F4 (4.1/0.9)
RNA.4 > 0.02513668:
:...ALT.48 > 0.6292135:
:...AST.1 <= 0.1011236:
: :...ALT.4 <= 0.1235955: F4 (4.5)
: : ALT.4 > 0.1235955: F3 (12.7/4.1)
: AST.1 > 0.1011236:
: :...Age <= 0: F1 (3.9)
: Age > 0:
: :...AST.1 <= 0.1685393:
: :...RBC <= 0.5050003: F3 (6/0.3)
: : RBC > 0.5050003: F2 (4.1)
: AST.1 > 0.1685393:
: :...ALT.36 > 0.8764045: [S1]
: ALT.36 <= 0.8764045:
: :...ALT.24 <= 0.2134831:
: :...ALT.4 <= 0.5955056:
: : :...RBC <= 0.6882355: F4 (9.3/1.7)
: : : RBC > 0.6882355: F3 (4.3/1.5)
: : ALT.4 > 0.5955056: [S2]
: ALT.24 > 0.2134831:
: :...ALT.24 <= 0.4269663: [S3]
: ALT.24 > 0.4269663:
: :...ALT.12 <= 0.1348315: [S4]
: ALT.12 > 0.1348315: [S5]
ALT.48 <= 0.6292135:
:...ALT.48 > 0.5842696:
:...Plat > 0.5311762: F2 (7.2)
: Plat <= 0.5311762:
: :...RBC > 0.9205809: F2 (2.7)
: RBC <= 0.9205809:
: :...ALT.36 <= 0.2808989: F3 (2.6/0.9)
: ALT.36 > 0.2808989: F4 (9.4/0.7)
ALT.48 <= 0.5842696:
:...BMI > 0.9230769:
:...ALT.36 > 0.8202247: F2 (3.5)
: ALT.36 <= 0.8202247:
: :...ALT.4 > 0.8651685: F2 (3/0.9)
: ALT.4 <= 0.8651685:
: :...ALT.36 <= 0.6853933: F4 (8.2/1.9)
: ALT.36 > 0.6853933: F3 (2.1)
BMI <= 0.9230769:
:...Age <= 0.2068966:
:...AST.1 <= 0.247191:
: :...Age <= 0: F2 (3.6/0.8)
: : Age > 0:
: : :...ALT.4 > 0.505618: F3 (7.9)
: : ALT.4 <= 0.505618: [S6]
: AST.1 > 0.247191:
: :...BMI <= 0.1538462:
: :...Plat <= 0.3357562: F1 (4.4/1)
: : Plat > 0.3357562: [S7]
: BMI > 0.1538462:
: :...ALT.1 > 0.9550562: F4 (4.9)
: ALT.1 <= 0.9550562:
: :...ALT.36 <= 0.3707865: [S8]
: ALT.36 > 0.3707865:
: :...ALT.4 <= 0.3033708: [S9]
: ALT.4 > 0.3033708: [S10]
Age > 0.2068966:
:...ALT.24 <= 0.3707865:
:...ALT.36 <= 0.6179775:
: :...ALT.48 > 0.4494382: [S11]
: : ALT.48 <= 0.4494382:
: : :...RBC > 0.1235278: F4 (21.5/2.1)
: : RBC <= 0.1235278: [S12]
: ALT.36 > 0.6179775:
: :...RNA.4 > 0.6600503: [S13]
: RNA.4 <= 0.6600503:
: :...Age <= 0.2758621: F3 (2.1)
: Age > 0.2758621: [S14]
ALT.24 > 0.3707865:
:...Age <= 0.2413793:
:...BMI <= 0.5384616: F4 (4.4)
: BMI > 0.5384616: F1 (2.7/0.9)
Age > 0.2413793:
:...RBC <= 0.1213149: [S15]
RBC > 0.1213149: [S16]
SubTree [S1]
ALT.after.24.w > 0.7826087: F2 (4.2/1.5)
ALT.after.24.w <= 0.7826087:
:...RBC <= 0.5174941: F2 (5.6/0.3)
RBC > 0.5174941: F3 (4.8/0.8)
SubTree [S2]
RNA.4 <= 0.2534222: F4 (2.6)
RNA.4 > 0.2534222:
:...ALT.36 <= 0.4044944: F3 (4.9)
ALT.36 > 0.4044944: F1 (4.6/2.4)
SubTree [S3]
RNA.4 <= 0.9264123: F1 (22.7/6.4)
RNA.4 > 0.9264123: F3 (3.6/1.3)
SubTree [S4]
ALT.4 > 0.6292135: F4 (4.3/2.1)
ALT.4 <= 0.6292135:
:...RNA.Base <= 0.4491626: F2 (4/1.2)
RNA.Base > 0.4491626: F3 (5.1)
SubTree [S5]
ALT.4 > 0.4157303: F1 (17.4/5.8)
ALT.4 <= 0.4157303:
:...RNA.Base <= 0.6258585:
:...AST.1 <= 0.6404495: F3 (4.8/0.8)
: AST.1 > 0.6404495: F2 (4.2/1)
RNA.Base > 0.6258585:
:...Age <= 0.3103448: F4 (6.7/0.7)
Age > 0.3103448: F1 (3.1/0.8)
SubTree [S6]
RNA.Base <= 0.5988144: F1 (6.8/0.7)
RNA.Base > 0.5988144: F3 (2.6/0.3)
SubTree [S7]
RNA.Base <= 0.5175647: F4 (8.5/1.5)
RNA.Base > 0.5175647: F2 (5.9)
SubTree [S8]
RBC > 0.6041094: F1 (6.8)
RBC <= 0.6041094:
:...ALT.24 <= 0.3820225: F1 (3.2/0.8)
ALT.24 > 0.3820225: F3 (2.9)
SubTree [S9]
ALT.36 <= 0.7078652: F4 (5.5/1)
ALT.36 > 0.7078652: F3 (4.3/0.7)
SubTree [S10]
ALT.36 <= 0.505618: F4 (4.8/0.7)
ALT.36 > 0.505618:
:...ALT.48 <= 0.3258427: F2 (5.6/1.7)
ALT.48 > 0.3258427: F1 (4.5/0.8)
SubTree [S11]
ALT.1 <= 0.4157303: F1 (5/0.8)
ALT.1 > 0.4157303: F3 (7.4/1.2)
SubTree [S12]
Age <= 0.3103448: F4 (2.3/1.2)
Age > 0.3103448: F2 (3.7)
SubTree [S13]
RNA.4 <= 0.9045269: F2 (5.8/0.7)
RNA.4 > 0.9045269: F4 (4.4/1.6)
SubTree [S14]
RBC <= 0.5629756: F2 (3.5/1.2)
RBC > 0.5629756: F1 (10.5/1)
SubTree [S15]
ALT.36 > 0.8876405: F1 (2.1)
ALT.36 <= 0.8876405:
:...ALT.48 <= 0.5617977: F3 (14.1/2.7)
ALT.48 > 0.5617977: F4 (2.9)
SubTree [S16]
ALT.after.24.w > 0.6521739:
:...WBC <= 0.2394072:
: :...BMI <= 0.3076923: F3 (2.8/0.7)
: : BMI > 0.3076923: F2 (5/1.6)
: WBC > 0.2394072:
: :...ALT.4 <= 0.6179775: F4 (16.7/4.1)
: ALT.4 > 0.6179775:
: :...Plat <= 0.5066878: F3 (3.5)
: Plat > 0.5066878: F4 (5.1/2.2)
ALT.after.24.w <= 0.6521739:
:...WBC <= 0.1493963: F4 (9.5/2.6)
WBC > 0.1493963:
:...ALT.36 <= 0.2921348: F3 (6.9)
ALT.36 > 0.2921348:
:...ALT.24 > 0.8539326:
:...Plat <= 0.2095301: F4 (2.4/1.2)
: Plat > 0.2095301: F2 (7.9)
ALT.24 <= 0.8539326:
:...ALT.1 <= 0.4494382:
:...ALT.12 <= 0.741573: F3 (9.4/0.7)
: ALT.12 > 0.741573: F4 (4.9)
ALT.1 > 0.4494382:
:...ALT.4 <= 0.3033708: F3 (5)
ALT.4 > 0.3033708:
:...RNA.Base > 0.5853523: F4 (5.5/2.7)
RNA.Base <= 0.5853523:
:...ALT.4 <= 0.7640449: F2 (6.3/0.9)
ALT.4 > 0.7640449: F1 (4.4/1.1)
----- Trial 6: -----
Decision tree:
ALT.48 > 0.9775281:
:...ALT.36 <= 0.1123596: F4 (4.7)
: ALT.36 > 0.1123596:
: :...ALT.4 <= 0.3820225: F2 (5.1/0.6)
: ALT.4 > 0.3820225:
: :...AST.1 <= 0.4269663: F3 (7.8)
: AST.1 > 0.4269663:
: :...Plat > 0.5482687: F4 (2.5)
: Plat <= 0.5482687:
: :...ALT.after.24.w <= 0.7826087: F3 (3.9/0.6)
: ALT.after.24.w > 0.7826087: F2 (2.4)
ALT.48 <= 0.9775281:
:...ALT.1 <= 0.08988764:
:...BMI <= 0.07692308:
: :...Age <= 0.5517241: F3 (5.4)
: : Age > 0.5517241: F4 (4.2/1.5)
: BMI > 0.07692308:
: :...ALT.1 > 0.06741573:
: :...ALT.after.24.w <= 0.5217391: F1 (8.1/0.6)
: : ALT.after.24.w > 0.5217391:
: : :...RNA.4 <= 0.4313345: F1 (2.9)
: : RNA.4 > 0.4313345: F4 (3.5/1.1)
: ALT.1 <= 0.06741573:
: :...ALT.1 > 0.05617978: F3 (5.8/1.3)
: ALT.1 <= 0.05617978:
: :...BMI <= 0.1538462:
: :...WBC <= 0.3489572: F1 (4.5)
: : WBC > 0.3489572: F4 (2.2)
: BMI > 0.1538462:
: :...Plat > 0.6101341:
: :...ALT.24 <= 0.6966292: F2 (18.1/4.7)
: : ALT.24 > 0.6966292: F1 (3.2/1.5)
: Plat <= 0.6101341:
: :...BMI <= 0.4615385: F3 (11.7/4.5)
: BMI > 0.4615385:
: :...Plat <= 0.3105634: F2 (6.3/2.1)
: Plat > 0.3105634: F1 (13.7/3.1)
ALT.1 > 0.08988764:
:...ALT.after.24.w > 0.7826087:
:...ALT.36 > 0.8764045:
: :...ALT.4 > 0.8764045: F1 (2.6)
: : ALT.4 <= 0.8764045:
: : :...RBC <= 0.3577825: F2 (2.5/1.1)
: : RBC > 0.3577825:
: : :...WBC <= 0.7923161: F4 (9.9/0.7)
: : WBC > 0.7923161: F2 (6.4/0.9)
: ALT.36 <= 0.8764045:
: :...BMI <= 0:
: :...Plat > 0.8699598: F2 (2.5)
: : Plat <= 0.8699598:
: : :...Plat <= 0.483833: F1 (3/0.3)
: : Plat > 0.483833: F4 (4.3)
: BMI > 0:
: :...Age <= 0.5862069:
: :...ALT.48 <= 0.2247191:
: : :...RBC <= 0.1783875: F2 (3.1/1.6)
: : : RBC > 0.1783875:
: : : :...ALT.12 > 0.5393258: F1 (14.2/3.1)
: : : ALT.12 <= 0.5393258:
: : : :...Plat <= 0.4785652: F3 (4.4)
: : : Plat > 0.4785652: F1 (2.1)
: : ALT.48 > 0.2247191:
: : :...ALT.24 > 0.8764045: F2 (5.5/1.9)
: : ALT.24 <= 0.8764045:
: : :...AST.1 > 0.8089887:
: : :...RNA.4 <= 0.736255: F1 (5/2.3)
: : : RNA.4 > 0.736255: F3 (3.8)
: : AST.1 <= 0.8089887:
: : :...ALT.24 <= 0.1235955:
: : :...RBC <= 0.8901707: F3 (5.7/0.3)
: : : RBC > 0.8901707: F1 (2.1/0.6)
: : ALT.24 > 0.1235955:
: : :...ALT.after.24.w <= 0.9130435:
: : :...WBC <= 0.6035126: F4 (17.1/3.4)
: : : WBC > 0.6035126:
: : : :...RBC <= 0.3504433: F4 (2.7)
: : : RBC > 0.3504433: F3 (6.9/0.6)
: : ALT.after.24.w > 0.9130435:
: : :...ALT.48 <= 0.4606742: F3 (6.3)
: : ALT.48 > 0.4606742:
: : :...RNA.4 <= 0.2636218: F1 (4.6/1.9)
: : RNA.4 > 0.2636218: F4 (6.6/0.3)
: Age > 0.5862069:
: :...ALT.48 <= 0.1011236: F3 (6.6)
: ALT.48 > 0.1011236:
: :...WBC <= 0.1086718: F2 (5.5/0.6)
: WBC > 0.1086718:
: :...RNA.4 > 0.5628213:
: :...ALT.48 > 0.8876405: F3 (3.5/1.4)
: : ALT.48 <= 0.8876405:
: : :...ALT.24 <= 0.2022472: F4 (2.3/0.3)
: : ALT.24 > 0.2022472: F1 (11.6/1.4)
: RNA.4 <= 0.5628213:
: :...AST.1 > 0.7752809:
: :...ALT.after.24.w <= 0.8695652: F2 (3.4)
: : ALT.after.24.w > 0.8695652: F3 (7.6/1)
: AST.1 <= 0.7752809:
: :...ALT.1 <= 0.2921348: F3 (5.8/0.9)
: ALT.1 > 0.2921348:
: :...ALT.after.24.w > 0.9565217: F3 (4.1/1.5)
: ALT.after.24.w <= 0.9565217:
: :...RNA.4 <= 0.07227951: F2 (3.3/0.9)
: RNA.4 > 0.07227951: F1 (7.9)
ALT.after.24.w <= 0.7826087:
:...ALT.after.24.w > 0.7391304:
:...ALT.1 <= 0.2247191: F1 (2.4/0.7)
: ALT.1 > 0.2247191:
: :...Plat <= 0.5515208:
: :...BMI <= 0.4615385: F3 (7.4/1.9)
: : BMI > 0.4615385: F2 (3/1.2)
: Plat > 0.5515208:
: :...BMI <= 0.6923077: F2 (9.1)
: BMI > 0.6923077:
: :...AST.1 <= 0.2808989: F2 (2.3)
: AST.1 > 0.2808989: F4 (4/0.3)
ALT.after.24.w <= 0.7391304:
:...ALT.4 > 0.9213483:
:...ALT.after.24.w <= 0.04347826:
: :...ALT.1 <= 0.9101124: F1 (4/0.6)
: : ALT.1 > 0.9101124: F3 (2.5)
: ALT.after.24.w > 0.04347826:
: :...RNA.Base > 0.7953583:
: :...RNA.Base <= 0.9279321: F4 (3.2)
: : RNA.Base > 0.9279321: F1 (3.2/0.7)
: RNA.Base <= 0.7953583:
: :...RNA.Base > 0.6712112: F2 (4.9)
: RNA.Base <= 0.6712112:
: :...AST.1 <= 0.1460674: F4 (3.8/1.1)
: AST.1 > 0.1460674:
: :...ALT.4 <= 0.9662921:
: :...AST.1 <= 0.6179775: F2 (7.7/0.6)
: : AST.1 > 0.6179775: F1 (4.4/0.7)
: ALT.4 > 0.9662921:
: :...ALT.12 <= 0.7078652: F2 (5.3/3)
: ALT.12 > 0.7078652: F1 (2.5)
ALT.4 <= 0.9213483:
:...BMI <= 0.4615385:
:...RNA.Base > 0.924148:
: :...RBC <= 0.4664646:
: : :...ALT.36 <= 0.6516854: F4 (5.8/0.6)
: : : ALT.36 > 0.6516854: F3 (2.3/0.9)
: : RBC > 0.4664646:
: : :...AST.1 <= 0.1685393: F3 (2.7/0.6)
: : AST.1 > 0.1685393: F1 (10.2/1.9)
: RNA.Base <= 0.924148:
: :...ALT.24 <= 0.2921348:
: :...RNA.Base <= 0.1408122:
: : :...AST.1 <= 0.4494382: F1 (4)
: : : AST.1 > 0.4494382: F3 (2.9/0.8)
: : RNA.Base > 0.1408122:
: : :...ALT.48 > 0.8876405:
: : :...ALT.36 <= 0.6404495: F2 (8.2/0.6)
: : : ALT.36 > 0.6404495: F3 (3.6)
: : ALT.48 <= 0.8876405:
: : :...Plat > 0.9539007: F3 (3.1)
: : Plat <= 0.9539007:
: : :...ALT.24 > 0.1011236:
: : :...RNA.Base <= 0.4851737:
: : : :...ALT.1 <= 0.9662921: F4 (8.2/1.6)
: : : : ALT.1 > 0.9662921: F1 (2.1)
: : : RNA.Base > 0.4851737:
: : : :...WBC <= 0.8659714: F2 (14.6/4.8)
: : : WBC > 0.8659714: F4 (2)
: : ALT.24 <= 0.1011236:
: : :...RNA.4 <= 0.3594661:
: : :...BMI > 0.1538462: F4 (2.5)
: : : BMI <= 0.1538462:
: : : :...ALT.1 <= 0.4269663: F4 (3.1/0.9)
: : : ALT.1 > 0.4269663: F3 (4.7)
: : RNA.4 > 0.3594661:
: : :...ALT.48 <= 0.08988764: F1 (2.8/1.3)
: : ALT.48 > 0.08988764:
: : :...ALT.24 > 0.05617978: F2 (5.7)
: : ALT.24 <= 0.05617978:
: : :...RBC <= 0.1471878: F2 (5.7/0.6)
: : RBC > 0.1471878: [S1]
: ALT.24 > 0.2921348:
: :...ALT.4 > 0.8089887:
: :...ALT.24 <= 0.7078652:
: : :...ALT.1 <= 0.8314607: F3 (15.1/1.6)
: : : ALT.1 > 0.8314607: F4 (2.4/0.9)
: : ALT.24 > 0.7078652:
: : :...ALT.12 <= 0.5505618: F2 (6.3/1.9)
: : ALT.12 > 0.5505618:
: : :...AST.1 <= 0.4494382: F4 (5)
: : AST.1 > 0.4494382: F3 (3/1.5)
: ALT.4 <= 0.8089887:
: :...ALT.48 <= 0.03370786:
: :...ALT.1 <= 0.1797753: F3 (2.6/0.9)
: : ALT.1 > 0.1797753: F4 (10.7/1.7)
: ALT.48 > 0.03370786:
: :...ALT.4 > 0.7640449: F1 (6.3/1.1)
: ALT.4 <= 0.7640449:
: :...Age > 0.5517241:
: :...RNA.Base > 0.7271253:
: : :...ALT.1 <= 0.9101124: F1 (6.9/0.8)
: : : ALT.1 > 0.9101124: F3 (2.2)
: : RNA.Base <= 0.7271253:
: : :...Age <= 0.6896552:
: : :...WBC <= 0.3068057: F3 (5.6)
: : : WBC > 0.3068057: [S2]
: : Age > 0.6896552:
: : :...ALT.48 <= 0.4606742: [S3]
: : ALT.48 > 0.4606742:
: : :...ALT.36 <= 0.5168539: [S4]
: : ALT.36 > 0.5168539: [S5]
: Age <= 0.5517241:
: :...ALT.24 > 0.8426966:
: :...BMI > 0.3846154: F2 (2.2)
: : BMI <= 0.3846154:
: : :...BMI <= 0.1538462: F3 (3.8/0.9)
: : BMI > 0.1538462: F1 (6/0.6)
: ALT.24 <= 0.8426966:
: :...RNA.Base > 0.6110709: F4 (17.9/2.9)
: RNA.Base <= 0.6110709:
: :...ALT.after.24.w > 0.6086956: [S6]
: ALT.after.24.w <= 0.6086956: [S7]
BMI > 0.4615385:
:...RNA.Base > 0.8605266:
:...RNA.4 <= 0.04654451: F3 (2.7/1.1)
: RNA.4 > 0.04654451:
: :...RBC > 0.896332: F4 (5.1/1.6)
: RBC <= 0.896332:
: :...RNA.4 <= 0.14795: F4 (3.2)
: RNA.4 > 0.14795:
: :...Age <= 0.06896552: F4 (2.8/0.7)
: Age > 0.06896552:
: :...ALT.48 > 0.8089887:
: :...Plat <= 0.2414594: F2 (3)
: : Plat > 0.2414594: F4 (4.6/0.6)
: ALT.48 <= 0.8089887:
: :...BMI > 0.7692308: F2 (11.6/0.6)
: BMI <= 0.7692308:
: :...ALT.36 <= 0.3258427: F1 (2.7)
: ALT.36 > 0.3258427: F2 (9.5/2.7)
RNA.Base <= 0.8605266:
:...ALT.after.24.w > 0.6086956:
:...BMI > 0.9230769: F3 (4.1/1.8)
: BMI <= 0.9230769:
: :...Plat > 0.8699598: F1 (4.5/0.3)
: Plat <= 0.8699598:
: :...Age <= 0.2068966: F4 (9.8/2.9)
: Age > 0.2068966:
: :...BMI > 0.7692308: F2 (4.2/0.9)
: BMI <= 0.7692308:
: :...ALT.after.24.w <= 0.6956522: F4 (5.7/2.6)
: ALT.after.24.w > 0.6956522: F1 (2.8)
ALT.after.24.w <= 0.6086956:
:...BMI <= 0.5384616:
:...RBC <= 0.2340792: F1 (5.6/2.3)
: RBC > 0.2340792:
: :...RBC <= 0.846908: F3 (16.1/2.6)
: RBC > 0.846908: F1 (2.4/0.9)
BMI > 0.5384616:
:...ALT.48 <= 0.04494382:
:...RNA.4 <= 0.528913: F4 (2.7)
: RNA.4 > 0.528913: F2 (5)
ALT.48 > 0.04494382:
:...ALT.after.24.w <= 0.04347826:
:...Age > 0.8275862: F1 (2.6)
: Age <= 0.8275862:
: :...ALT.4 <= 0.2134831: F1 (5.5/2)
: ALT.4 > 0.2134831: F3 (22.4/8.5)
ALT.after.24.w > 0.04347826:
:...Plat > 0.9235899:
:...ALT.24 <= 0.6741573: F2 (4.5)
: ALT.24 > 0.6741573: F4 (4.3/1.1)
Plat <= 0.9235899:
:...ALT.1 > 0.8764045: [S8]
ALT.1 <= 0.8764045:
:...ALT.1 <= 0.3820225:
:...BMI <= 0.6153846: [S9]
: BMI > 0.6153846:
: :...WBC > 0.8983535: F2 (2.7/0.6)
: WBC <= 0.8983535:
: :...BMI > 0.8461539: [S10]
: BMI <= 0.8461539: [S11]
ALT.1 > 0.3820225:
:...ALT.12 > 0.8539326: F3 (11.3/2.2)
ALT.12 <= 0.8539326:
:...Plat <= 0.09056508: [S12]
Plat > 0.09056508:
:...BMI > 0.9230769: [S13]
BMI <= 0.9230769: [S14]
SubTree [S1]
ALT.24 <= 0: F2 (2.3/0.9)
ALT.24 > 0: F3 (5.8/0.9)
SubTree [S2]
ALT.48 <= 0.6067415: F1 (4.3/2.1)
ALT.48 > 0.6067415: F2 (4)
SubTree [S3]
RNA.4 <= 0.170616: F4 (6.3)
RNA.4 > 0.170616:
:...ALT.4 <= 0.5505618: F2 (8.4/1.6)
ALT.4 > 0.5505618: F4 (3.7/0.9)
SubTree [S4]
RBC <= 0.3884507: F1 (4.3/1.4)
RBC > 0.3884507: F2 (4.1)
SubTree [S5]
ALT.48 <= 0.6853933: F3 (5/0.3)
ALT.48 > 0.6853933:
:...RNA.Base <= 0.1841276: F4 (3.9)
RNA.Base > 0.1841276: F3 (2.7/0.6)
SubTree [S6]
ALT.48 <= 0.6179775: F4 (7.8/1.1)
ALT.48 > 0.6179775: F1 (2.3/0.6)
SubTree [S7]
ALT.36 <= 0.07865169: F4 (4.2/1.7)
ALT.36 > 0.07865169:
:...ALT.4 > 0.7191011: F4 (2.8/0.6)
ALT.4 <= 0.7191011:
:...ALT.36 > 0.9775281: F4 (3.4/1.9)
ALT.36 <= 0.9775281:
:...Age <= 0.1724138: F1 (11.6/3.1)
Age > 0.1724138:
:...ALT.24 > 0.5393258: F2 (6.2/0.3)
ALT.24 <= 0.5393258:
:...ALT.after.24.w > 0.3913043: F1 (3.9/0.9)
ALT.after.24.w <= 0.3913043:
:...Age <= 0.4137931: F2 (3.1)
Age > 0.4137931: F1 (5.4/0.6)
SubTree [S8]
ALT.after.24.w <= 0.4782609: F1 (7/0.8)
ALT.after.24.w > 0.4782609: F3 (4.1/1.1)
SubTree [S9]
ALT.48 <= 0.8651685: F2 (4.3)
ALT.48 > 0.8651685: F3 (2.6/0.7)
SubTree [S10]
ALT.48 > 0.5168539: F1 (6.8/0.7)
ALT.48 <= 0.5168539:
:...ALT.4 <= 0.3932584: F3 (4.9)
ALT.4 > 0.3932584: F1 (2.7/1)
SubTree [S11]
RNA.Base <= 0.0669725: F3 (2.9)
RNA.Base > 0.0669725:
:...ALT.24 <= 0.1348315: F1 (2.7)
ALT.24 > 0.1348315:
:...Plat <= 0.5482687: F4 (16.2/4.6)
Plat > 0.5482687: F3 (3.9/1.6)
SubTree [S12]
BMI > 0.9230769: F3 (2.7)
BMI <= 0.9230769:
:...ALT.1 <= 0.5393258: F2 (5.2)
ALT.1 > 0.5393258:
:...ALT.12 <= 0.3595506: F2 (3.4)
ALT.12 > 0.3595506: F3 (2.9)
SubTree [S13]
ALT.4 <= 0.3483146: F4 (3.9)
ALT.4 > 0.3483146: F2 (4.6/0.9)
SubTree [S14]
ALT.after.24.w <= 0.2173913:
:...ALT.24 <= 0.6853933: F2 (12.5/3.1)
: ALT.24 > 0.6853933: F3 (2.4)
ALT.after.24.w > 0.2173913:
:...AST.1 <= 0.1348315:
:...RNA.4 <= 0.6053365: F4 (2.7)
: RNA.4 > 0.6053365:
: :...RBC <= 0.512243: F4 (3/1.5)
: RBC > 0.512243: F2 (4.2)
AST.1 > 0.1348315:
:...ALT.after.24.w <= 0.3478261: F1 (10.3/2.2)
ALT.after.24.w > 0.3478261:
:...AST.1 <= 0.3370787: F1 (6.6/2.2)
AST.1 > 0.3370787:
:...RNA.Base <= 0.08821014: F2 (2.7)
RNA.Base > 0.08821014: F3 (17.1/5.2)
----- Trial 7: -----
Decision tree:
ALT.1 <= 0.1235955:
:...ALT.36 <= 0.05617978:
: :...RNA.Base <= 0.6427184: F3 (3.6)
: : RNA.Base > 0.6427184: F4 (6.4/0.9)
: ALT.36 > 0.05617978:
: :...ALT.1 <= 0:
: :...RNA.4 <= 0.2575646: F4 (4.1/1.7)
: : RNA.4 > 0.2575646:
: : :...ALT.36 <= 0.5842696: F1 (6.9/1.6)
: : ALT.36 > 0.5842696: F2 (2.5)
: ALT.1 > 0:
: :...Age > 0.9310345: F1 (4.8/1.9)
: Age <= 0.9310345:
: :...ALT.12 <= 0.03370786: F2 (5.6/2)
: ALT.12 > 0.03370786:
: :...ALT.after.24.w > 0.8260869:
: :...AST.1 <= 0.1910112: F1 (4.6)
: : AST.1 > 0.1910112:
: : :...ALT.36 > 0.6853933: F1 (3.4)
: : ALT.36 <= 0.6853933:
: : :...ALT.after.24.w <= 0.9130435: F4 (5/1.4)
: : ALT.after.24.w > 0.9130435: F3 (5.9)
: ALT.after.24.w <= 0.8260869:
: :...ALT.24 <= 0.1910112: F2 (8.2/1.7)
: ALT.24 > 0.1910112:
: :...RNA.4 <= 0.03091095: F2 (3.1)
: RNA.4 > 0.03091095:
: :...RNA.4 <= 0.6620965:
: :...RBC <= 0.3964039:
: : :...ALT.1 <= 0.1123596: F3 (17.8/2.7)
: : : ALT.1 > 0.1123596: F1 (2.4/1.1)
: : RBC > 0.3964039:
: : :...WBC <= 0.6289791: F1 (17.9/4.6)
: : WBC > 0.6289791: F3 (8/2.7)
: RNA.4 > 0.6620965:
: :...ALT.after.24.w > 0.5652174: F3 (3.9/1.9)
: ALT.after.24.w <= 0.5652174:
: :...ALT.after.24.w <= 0.1304348: F2 (4.9/1.3)
: ALT.after.24.w > 0.1304348:
: :...ALT.after.24.w <= 0.4782609: F1 (11.6/2)
: ALT.after.24.w > 0.4782609: F2 (2.5)
ALT.1 > 0.1235955:
:...BMI > 0.6923077:
:...ALT.4 > 0.9213483:
: :...ALT.48 <= 0.752809: F2 (9.7/1.5)
: : ALT.48 > 0.752809: F1 (2.4/0.5)
: ALT.4 <= 0.9213483:
: :...ALT.36 <= 0: F2 (7.9/1.7)
: ALT.36 > 0:
: :...ALT.36 > 0.9213483:
: :...ALT.4 > 0.4269663: F1 (3.6/1.7)
: : ALT.4 <= 0.4269663:
: : :...RNA.4 <= 0.59883: F1 (2.4/0.6)
: : RNA.4 > 0.59883: F4 (5.2)
: ALT.36 <= 0.9213483:
: :...ALT.36 > 0.7640449:
: :...BMI > 0.8461539:
: : :...RBC <= 0.6882355: F2 (13.1/3.9)
: : : RBC > 0.6882355: F3 (5.6/1.3)
: : BMI <= 0.8461539:
: : :...WBC <= 0.4462129:
: : :...RBC <= 0.6904467: F4 (3/0.5)
: : : RBC > 0.6904467: F3 (2.9/0.2)
: : WBC > 0.4462129:
: : :...ALT.after.24.w <= 0.6521739: F2 (8.1/0.8)
: : ALT.after.24.w > 0.6521739: F3 (3.6/0.8)
: ALT.36 <= 0.7640449:
: :...ALT.24 <= 0.1797753:
: :...RNA.Base <= 0.2276536:
: : :...AST.1 <= 0.4719101: F1 (3.1/0.6)
: : : AST.1 > 0.4719101:
: : : :...ALT.1 <= 0.4044944: F1 (2.7/0.5)
: : : ALT.1 > 0.4044944: F4 (6.8)
: : RNA.Base > 0.2276536:
: : :...RNA.Base <= 0.4238328: F2 (5.5/0.9)
: : RNA.Base > 0.4238328:
: : :...Age <= 0.2413793: F3 (3.5/0.8)
: : Age > 0.2413793: F4 (15.9/4.6)
: ALT.24 > 0.1797753:
: :...Plat <= 0.1512016:
: :...ALT.24 <= 0.6516854:
: : :...ALT.24 > 0.4494382: F4 (6.8/0.5)
: : : ALT.24 <= 0.4494382:
: : : :...AST.1 <= 0.1235955: F4 (2.6)
: : : AST.1 > 0.1235955: F3 (7.9/1.1)
: : ALT.24 > 0.6516854:
: : :...ALT.12 > 0.8202247: F3 (4.6/2.1)
: : ALT.12 <= 0.8202247:
: : :...ALT.36 <= 0.4494382: F3 (2.5/0.6)
: : ALT.36 > 0.4494382: F2 (4)
: Plat > 0.1512016:
: :...Plat <= 0.2486081:
: :...WBC <= 0.3002195: F1 (3.9/0.8)
: : WBC > 0.3002195: F3 (9.1/1)
: Plat > 0.2486081:
: :...RNA.4 > 0.9397534: F2 (6.9/0.9)
: RNA.4 <= 0.9397534:
: :...ALT.24 > 0.9213483:
: :...ALT.48 > 0.5955056: F3 (5.7/0.9)
: : ALT.48 <= 0.5955056:
: : :...Plat <= 0.3629422: F3 (2.3)
: : Plat > 0.3629422: F2 (10.9/3.4)
: ALT.24 <= 0.9213483:
: :...ALT.4 <= 0.08988764: F1 (10.7/2.2)
: ALT.4 > 0.08988764:
: :...Plat <= 0.5191718:
: :...WBC <= 0.1385291: F4 (2.7/0.5)
: : WBC > 0.1385291:
: : :...BMI <= 0.8461539:
: : :...Age <= 0.1724138: F1 (2.8)
: : : Age > 0.1724138: F4 (4.2/1.6)
: : BMI > 0.8461539: [S1]
: Plat > 0.5191718:
: :...ALT.24 <= 0.258427: F3 (5)
: ALT.24 > 0.258427:
: :...AST.1 > 0.7865168: F3 (6.1/1.7)
: AST.1 <= 0.7865168:
: :...Age > 0.5862069: [S2]
: Age <= 0.5862069:
: :...RNA.4 <= 0.6912616: [S3]
: RNA.4 > 0.6912616: [S4]
BMI <= 0.6923077:
:...Age > 0.9655172:
:...RBC <= 0.1004402: F3 (3.4)
: RBC > 0.1004402:
: :...AST.1 <= 0.4831461: F1 (4.4/0.4)
: AST.1 > 0.4831461: F2 (8.6/1.8)
Age <= 0.9655172:
:...ALT.after.24.w <= 0:
:...ALT.1 <= 0.4494382: F4 (4.5/1.9)
: ALT.1 > 0.4494382:
: :...ALT.36 <= 0.08988764: F2 (2.8)
: ALT.36 > 0.08988764:
: :...ALT.4 <= 0.2696629: F2 (2.6/0.9)
: ALT.4 > 0.2696629:
: :...RNA.Base <= 0.8369943: F1 (10.3/0.7)
: RNA.Base > 0.8369943: F3 (2.7/0.6)
ALT.after.24.w > 0:
:...RNA.4 <= 0.04120711:
:...ALT.1 > 0.8202247:
: :...RNA.Base <= 0.3972525: F2 (2.4)
: : RNA.Base > 0.3972525: F1 (4.1/0.2)
: ALT.1 <= 0.8202247:
: :...Plat <= 0.258964: F4 (5)
: Plat > 0.258964:
: :...ALT.24 <= 0.4382023: F4 (5.2/1.3)
: ALT.24 > 0.4382023: F1 (4.3)
RNA.4 > 0.04120711:
:...WBC <= 0.01855104:
:...Plat > 0.7840106: F2 (3.4/1.3)
: Plat <= 0.7840106:
: :...RNA.Base <= 0.5799838: F3 (4.9)
: RNA.Base > 0.5799838: F2 (5.2/1.2)
WBC > 0.01855104:
:...AST.1 <= 0.02247191:
:...ALT.12 > 0.741573: F1 (4/0.5)
: ALT.12 <= 0.741573:
: :...ALT.24 <= 0.06741573: F1 (2.3)
: ALT.24 > 0.06741573: F4 (6.9)
AST.1 > 0.02247191:
:...RNA.Base <= 0.5254951:
:...ALT.after.24.w > 0.7826087:
: :...Plat <= 0.1760197:
: : :...BMI <= 0.3076923: F1 (4.9/0.8)
: : : BMI > 0.3076923: F2 (2.8/1.1)
: : Plat > 0.1760197:
: : :...ALT.36 > 0.8651685: F2 (4.6/2.1)
: : ALT.36 <= 0.8651685:
: : :...ALT.48 <= 0.2134831:
: : :...BMI <= 0.2307692: F1 (4.1/0.7)
: : : BMI > 0.2307692: F4 (5.5/0.6)
: : ALT.48 > 0.2134831:
: : :...Age > 0.7241379: F1 (5.5/2.7)
: : Age <= 0.7241379:
: : :...ALT.1 <= 0.4157303: F3 (7.4/0.2)
: : ALT.1 > 0.4157303:
: : :...WBC <= 0.7364435: F3 (6.9/1.7)
: : WBC > 0.7364435: F4 (4.5/0.5)
: ALT.after.24.w <= 0.7826087:
: :...ALT.12 <= 0.3483146:
: :...RBC <= 0.169807:
: : :...RNA.4 <= 0.2149778: F1 (2.4)
: : : RNA.4 > 0.2149778: F2 (5.4)
: : RBC > 0.169807:
: : :...ALT.12 > 0.3033708:
: : :...BMI <= 0.2307692: F1 (3.4)
: : : BMI > 0.2307692: F2 (3.2/0.9)
: : ALT.12 <= 0.3033708:
: : :...RNA.Base <= 0.1011311:
: : :...ALT.48 <= 0.4157303: F4 (2.6)
: : : ALT.48 > 0.4157303: F1 (6.4/2.2)
: : RNA.Base > 0.1011311:
: : :...Plat <= 0.2432353:
: : :...Plat <= 0.1760197: F3 (3.2)
: : : Plat > 0.1760197: F4 (3.9/0.6)
: : Plat > 0.2432353:
: : :...ALT.36 <= 0.3483146: [S5]
: : ALT.36 > 0.3483146: [S6]
: ALT.12 > 0.3483146:
: :...ALT.4 <= 0.3146068:
: :...Age > 0.862069: F4 (6/0.6)
: : Age <= 0.862069:
: : :...ALT.1 <= 0.494382:
: : :...ALT.4 > 0.2696629: F3 (6.4)
: : : ALT.4 <= 0.2696629:
: : : :...RNA.4 <= 0.2005842: F1 (3.1/1.5)
: : : RNA.4 > 0.2005842:
: : : :...BMI <= 0.3846154: F4 (12/1.3)
: : : BMI > 0.3846154: F3 (2.5/0.6)
: : ALT.1 > 0.494382: [S7]
: ALT.4 > 0.3146068:
: :...ALT.4 <= 0.5393258:
: :...Age <= 0.137931: F4 (3.4/1.3)
: : Age > 0.137931: F2 (22.7/5.6)
: ALT.4 > 0.5393258:
: :...RNA.4 <= 0.170616: F4 (6.7/1.6)
: RNA.4 > 0.170616:
: :...Age > 0.7931035:
: :...BMI <= 0.3076923: F3 (7.8/0.6)
: : BMI > 0.3076923: [S8]
: Age <= 0.7931035:
: :...WBC > 0.5120746:
: :...Age <= 0: F4 (2.5/1.2)
: : Age > 0: [S9]
: WBC <= 0.5120746:
: :...Age <= 0.5172414: [S10]
: Age > 0.5172414: [S11]
RNA.Base > 0.5254951:
:...RNA.4 <= 0.2984472:
:...ALT.1 > 0.6179775:
: :...Plat > 0.5436003:
: : :...BMI <= 0.2307692: F2 (2.8/0.5)
: : : BMI > 0.2307692: F4 (14.2/4.8)
: : Plat <= 0.5436003:
: : :...WBC <= 0.3489572:
: : :...AST.1 <= 0.2134831: F1 (2.5/0.7)
: : : AST.1 > 0.2134831: F4 (4.2/1.1)
: : WBC > 0.3489572:
: : :...ALT.12 <= 0.2134831: F1 (2.2/0.5)
: : ALT.12 > 0.2134831: F3 (9)
: ALT.1 <= 0.6179775:
: :...Plat > 0.8774456:
: :...ALT.12 <= 0.5505618: F2 (3.2)
: : ALT.12 > 0.5505618: F3 (3.5/1.3)
: Plat <= 0.8774456:
: :...BMI <= 0.07692308: F4 (4.8/0.9)
: BMI > 0.07692308:
: :...RNA.4 > 0.2695684: F2 (5.4)
: RNA.4 <= 0.2695684:
: :...Age <= 0.5517241: F2 (6.1/1.7)
: Age > 0.5517241: F4 (10.8/1.3)
RNA.4 > 0.2984472:
:...AST.1 > 0.6966292:
:...ALT.48 <= 0.1910112:
: :...Age > 0.6551724: F3 (2)
: : Age <= 0.6551724:
: : :...RNA.4 <= 0.8416881: F4 (8.9/2.3)
: : RNA.4 > 0.8416881: F2 (2.4)
: ALT.48 > 0.1910112:
: :...ALT.after.24.w <= 0.173913: F3 (4.2/0.5)
: ALT.after.24.w > 0.173913:
: :...ALT.4 <= 0.3033708:
: :...ALT.1 <= 0.4719101: F2 (4.2)
: : ALT.1 > 0.4719101: F3 (4.8/0.5)
: ALT.4 > 0.3033708:
: :...RNA.Base <= 0.6028808:
: :...Age <= 0.2758621: F1 (2.3)
: : Age > 0.2758621: F3 (4.2/0.5)
: RNA.Base > 0.6028808:
: :...ALT.12 > 0.752809: F1 (8.3/1)
: ALT.12 <= 0.752809:
: :...RBC > 0.803508: F4 (4.5/1.2)
: RBC <= 0.803508: [S12]
AST.1 <= 0.6966292:
:...ALT.36 <= 0.08988764:
:...ALT.1 > 0.8764045: F4 (2.1)
: ALT.1 <= 0.8764045:
: :...RBC <= 0.09045705: F1 (2)
: RBC > 0.09045705:
: :...ALT.48 <= 0.6516854: F3 (5.5/1.3)
: ALT.48 > 0.6516854: F2 (4.6/0.9)
ALT.36 > 0.08988764:
:...ALT.12 <= 0.1123596:
:...ALT.12 <= 0.05617978: F3 (3.6/0.7)
: ALT.12 > 0.05617978: F4 (4.9/0.5)
ALT.12 > 0.1123596:
:...Age > 0.6551724:
:...ALT.36 <= 0.3033708: F1 (10.6/1.3)
: ALT.36 > 0.3033708:
: :...ALT.1 <= 0.4606742: [S13]
: ALT.1 > 0.4606742: [S14]
Age <= 0.6551724:
:...ALT.4 > 0.8651685: F3 (4.5)
ALT.4 <= 0.8651685:
:...ALT.48 > 0.9438202: F2 (3.2/0.6)
ALT.48 <= 0.9438202:
:...ALT.24 <= 0.1235955: [S15]
ALT.24 > 0.1235955: [S16]
SubTree [S1]
RNA.Base <= 0.4306309: F1 (4.7)
RNA.Base > 0.4306309:
:...ALT.36 <= 0.6629214: F2 (7.8/1.6)
ALT.36 > 0.6629214: F1 (2.5)
SubTree [S2]
ALT.48 <= 0.2022472: F4 (2.2)
ALT.48 > 0.2022472: F2 (4.9)
SubTree [S3]
WBC > 0.6816685: F1 (4.6/0.8)
WBC <= 0.6816685:
:...AST.1 <= 0.2359551: F1 (3.2/0.7)
AST.1 > 0.2359551: F3 (7/1.4)
SubTree [S4]
ALT.24 > 0.752809: F4 (2.8)
ALT.24 <= 0.752809:
:...AST.1 <= 0.2808989: F2 (4.3)
AST.1 > 0.2808989: F1 (2.2)
SubTree [S5]
ALT.4 <= 0.7191011: F3 (4.7/0.5)
ALT.4 > 0.7191011: F2 (2.6/1.2)
SubTree [S6]
ALT.48 > 0.6629214: F2 (11.5/2.1)
ALT.48 <= 0.6629214:
:...RBC <= 0.5629756: F2 (4.2/0.5)
RBC > 0.5629756: F1 (2.6)
SubTree [S7]
ALT.after.24.w > 0.6521739: F4 (4.3/1.3)
ALT.after.24.w <= 0.6521739:
:...WBC > 0.584303: F3 (10.2/1.3)
WBC <= 0.584303:
:...ALT.36 <= 0.6292135: F2 (9.1/1)
ALT.36 > 0.6292135: F3 (2.8/1.3)
SubTree [S8]
ALT.12 <= 0.8764045: F1 (5.2/0.5)
ALT.12 > 0.8764045: F3 (2.1)
SubTree [S9]
RNA.4 <= 0.569367: F3 (13.6/2.5)
RNA.4 > 0.569367: F2 (6.1/1.6)
SubTree [S10]
WBC <= 0.1351262: F4 (3.2/0.9)
WBC > 0.1351262:
:...BMI <= 0.2307692: F4 (3.6/1.2)
BMI > 0.2307692: F1 (8.3/1.7)
SubTree [S11]
ALT.12 <= 0.5168539: F3 (2.1)
ALT.12 > 0.5168539:
:...Age <= 0.7241379: F2 (5.4/0.5)
Age > 0.7241379: F4 (3.1/0.9)
SubTree [S12]
ALT.12 <= 0.2921348: F1 (6.4/1.2)
ALT.12 > 0.2921348: F2 (5.7)
SubTree [S13]
ALT.36 <= 0.505618: F2 (2.1)
ALT.36 > 0.505618: F1 (5.4/1.8)
SubTree [S14]
RNA.Base <= 0.9733889: F4 (13.6/0.5)
RNA.Base > 0.9733889: F1 (2.5)
SubTree [S15]
RNA.4 <= 0.6667932: F3 (2.8)
RNA.4 > 0.6667932: F1 (3.9/1.1)
SubTree [S16]
Plat > 0.8968086: F3 (2.1)
Plat <= 0.8968086:
:...ALT.after.24.w <= 0.08695652: F2 (4.3/2.5)
ALT.after.24.w > 0.08695652:
:...ALT.1 <= 0.3595506: F4 (5.6/1.6)
ALT.1 > 0.3595506:
:...RNA.4 <= 0.4365587: F4 (5.2)
RNA.4 > 0.4365587:
:...RBC > 0.6150659: F4 (10.7/1.5)
RBC <= 0.6150659:
:...ALT.12 <= 0.988764: F1 (14.8/0.5)
ALT.12 > 0.988764: F4 (2.3)
----- Trial 8: -----
Decision tree:
WBC <= 0.03084522:
:...RBC > 0.8945807: F1 (5.4)
: RBC <= 0.8945807:
: :...WBC > 0.01613611:
: :...BMI <= 0.07692308: F1 (4.1)
: : BMI > 0.07692308: F3 (8.6/3.3)
: WBC <= 0.01613611:
: :...BMI > 0.7692308: F2 (3.5/1.2)
: BMI <= 0.7692308:
: :...RNA.4 <= 0.4198684: F3 (7/1)
: RNA.4 > 0.4198684: F2 (5.3/1)
WBC > 0.03084522:
:...ALT.48 > 0.9438202:
:...Plat > 0.9034327: F1 (3.5/0.2)
: Plat <= 0.9034327:
: :...ALT.4 <= 0.1460674:
: :...ALT.1 <= 0.6067415: F3 (4.1)
: : ALT.1 > 0.6067415: F2 (3.8/1.6)
: ALT.4 > 0.1460674:
: :...ALT.48 > 0.9662921:
: :...ALT.36 <= 0.5168539: F4 (14.5/2.1)
: : ALT.36 > 0.5168539:
: : :...WBC <= 0.5047201: F2 (8.7/2.6)
: : WBC > 0.5047201: F3 (2.9)
: ALT.48 <= 0.9662921:
: :...Age <= 0.3448276: F2 (5.1/1.2)
: Age > 0.3448276:
: :...ALT.36 > 0.6179775: F4 (6.5/1)
: ALT.36 <= 0.6179775:
: :...Age <= 0.6206896: F4 (3.8/1.6)
: Age > 0.6206896: F2 (8.5)
ALT.48 <= 0.9438202:
:...BMI <= 0.4615385:
:...AST.1 > 0.7191011:
: :...ALT.1 <= 0.05617978:
: : :...RBC <= 0.512243: F3 (4)
: : : RBC > 0.512243: F1 (4.7)
: : ALT.1 > 0.05617978:
: : :...ALT.48 <= 0.08988764:
: : :...RNA.4 <= 0.4694727: F3 (7/2.1)
: : : RNA.4 > 0.4694727:
: : : :...RBC <= 0.7754056: F2 (5.8/1.1)
: : : RBC > 0.7754056: F4 (4.4)
: : ALT.48 > 0.08988764:
: : :...RNA.4 <= 0.1684916:
: : :...Plat > 0.6043042: F2 (4.3/1.5)
: : : Plat <= 0.6043042:
: : : :...RNA.4 <= 0.1055954: F4 (4.6)
: : : RNA.4 > 0.1055954: F1 (2.8)
: : RNA.4 > 0.1684916:
: : :...RNA.4 > 0.8075259:
: : :...ALT.after.24.w <= 0.2608696: F2 (2.1/1)
: : : ALT.after.24.w > 0.2608696:
: : : :...ALT.24 <= 0.6179775: F4 (7.6/1.4)
: : : ALT.24 > 0.6179775:
: : : :...RNA.Base <= 0.5175647: F3 (2.4)
: : : RNA.Base > 0.5175647: F1 (5.8/1.2)
: : RNA.4 <= 0.8075259:
: : :...BMI <= 0.1538462:
: : :...ALT.36 > 0.752809: F3 (4.7/1.4)
: : : ALT.36 <= 0.752809:
: : : :...ALT.36 <= 0.3258427: F3 (9.2/1.2)
: : : ALT.36 > 0.3258427: F2 (11.6/1.2)
: : BMI > 0.1538462:
: : :...RBC > 0.8821443: F1 (3.7)
: : RBC <= 0.8821443:
: : :...AST.1 <= 0.7640449: F1 (2.7/0.4)
: : AST.1 > 0.7640449:
: : :...ALT.after.24.w <= 0.2608696: F3 (4.9/1.6)
: : ALT.after.24.w > 0.2608696:
: : :...RBC > 0.7366652: F3 (3.2)
: : RBC <= 0.7366652:
: : :...RBC > 0.4163593: F2 (8.8/1.9)
: : RBC <= 0.4163593:
: : :...ALT.36 <= 0.6067415: F3 (5.6/0.8)
: : ALT.36 > 0.6067415: F2 (3.8)
: AST.1 <= 0.7191011:
: :...Age <= 0.137931:
: :...ALT.after.24.w <= 0.4782609:
: : :...RNA.4 <= 0.9675812: F1 (18.1/5)
: : : RNA.4 > 0.9675812: F3 (2.2)
: : ALT.after.24.w > 0.4782609:
: : :...RNA.4 <= 0.7286625: F3 (17.8/7.2)
: : RNA.4 > 0.7286625: F1 (7.3/2)
: Age > 0.137931:
: :...RBC > 0.8990407:
: :...RBC <= 0.9731978: F3 (17.3/3.3)
: : RBC > 0.9731978:
: : :...ALT.1 <= 0.1460674: F4 (3)
: : ALT.1 > 0.1460674:
: : :...ALT.36 <= 0.5842696: F1 (2.5/0.6)
: : ALT.36 > 0.5842696: F2 (5/1.8)
: RBC <= 0.8990407:
: :...ALT.48 > 0.8764045:
: :...RNA.Base <= 0.1147347: F1 (3.5/1.5)
: : RNA.Base > 0.1147347: F2 (12.5/4.3)
: ALT.48 <= 0.8764045:
: :...RNA.4 <= 0.2949855:
: :...ALT.after.24.w > 0.9565217: F3 (4.5)
: : ALT.after.24.w <= 0.9565217:
: : :...ALT.after.24.w > 0.8695652: F1 (5.5/1.8)
: : ALT.after.24.w <= 0.8695652:
: : :...ALT.12 > 0.8988764:
: : :...ALT.36 <= 0.7640449: F3 (4.1/2.1)
: : : ALT.36 > 0.7640449: F1 (4.1)
: : ALT.12 <= 0.8988764:
: : :...BMI > 0.3846154:
: : :...RBC <= 0.2986933: F4 (3.8)
: : : RBC > 0.2986933: F2 (4.3/1.8)
: : BMI <= 0.3846154:
: : :...Plat > 0.8278394: F3 (5.6/0.6)
: : Plat <= 0.8278394:
: : :...ALT.4 > 0.6067415:
: : :...ALT.48 <= 0.3483146: F2 (7.3/1.1)
: : : ALT.48 > 0.3483146: F4 (8.1/1.7)
: : ALT.4 <= 0.6067415:
: : :...RNA.Base > 0.8355365: F3 (3.3)
: : RNA.Base <= 0.8355365: [S1]
: RNA.4 > 0.2949855:
: :...RNA.4 <= 0.4665918:
: :...ALT.after.24.w <= 0.1304348: F4 (5.9/2.7)
: : ALT.after.24.w > 0.1304348: F1 (28.4/7.4)
: RNA.4 > 0.4665918:
: :...Age <= 0.1724138:
: :...RBC <= 0.4158286: F2 (3)
: : RBC > 0.4158286: F4 (3.4)
: Age > 0.1724138:
: :...Age <= 0.2068966: F1 (6/1.2)
: Age > 0.2068966:
: :...RNA.4 <= 0.5406513:
: :...ALT.48 > 0.7191011: F1 (5.1/1.5)
: : ALT.48 <= 0.7191011:
: : :...ALT.24 <= 0.7865168: F3 (7.9/1.9)
: : ALT.24 > 0.7865168: F2 (2.8/1.2)
: RNA.4 > 0.5406513:
: :...Plat > 0.8854336:
: :...ALT.48 <= 0.6067415: F1 (5.4/0.9)
: : ALT.48 > 0.6067415: F3 (2.5/0.7)
: Plat <= 0.8854336:
: :...Age <= 0.3793103: [S2]
: Age > 0.3793103:
: :...RNA.Base > 0.6345674: [S3]
: RNA.Base <= 0.6345674:
: :...ALT.4 > 0.7078652: [S4]
: ALT.4 <= 0.7078652: [S5]
BMI > 0.4615385:
:...ALT.after.24.w > 0.4347826:
:...ALT.after.24.w <= 0.4782609:
: :...ALT.48 > 0.752809: F3 (3.3)
: : ALT.48 <= 0.752809:
: : :...AST.1 <= 0.258427: F2 (5.7/2.8)
: : AST.1 > 0.258427: F1 (8.9/0.6)
: ALT.after.24.w > 0.4782609:
: :...ALT.4 <= 0.4831461:
: :...RBC > 0.9237997: F2 (7/1.1)
: : RBC <= 0.9237997:
: : :...Plat <= 0.2392788:
: : :...ALT.24 <= 0.1235955: F2 (3.6/0.2)
: : : ALT.24 > 0.1235955:
: : : :...RNA.4 > 0.8680305: F3 (3)
: : : RNA.4 <= 0.8680305:
: : : :...ALT.12 <= 0.1573034: F3 (4.3/1.6)
: : : ALT.12 > 0.1573034: F4 (12.1/1.1)
: : Plat > 0.2392788:
: : :...WBC <= 0.1654226:
: : :...RNA.Base <= 0.3461807: F2 (2.8)
: : : RNA.Base > 0.3461807:
: : : :...ALT.4 <= 0.3033708: F1 (3.2/0.9)
: : : ALT.4 > 0.3033708: F3 (3)
: : WBC > 0.1654226:
: : :...ALT.36 <= 0.3146068:
: : :...ALT.after.24.w <= 0.6956522:
: : : :...ALT.after.24.w <= 0.5217391: F1 (3.3)
: : : : ALT.after.24.w > 0.5217391: F2 (5.1/0.7)
: : : ALT.after.24.w > 0.6956522:
: : : :...AST.1 > 0.6966292: F4 (7.5/0.6)
: : : AST.1 <= 0.6966292:
: : : :...Plat <= 0.4018329: F4 (2.1)
: : : Plat > 0.4018329: F1 (10.6/1.7)
: : ALT.36 > 0.3146068:
: : :...ALT.4 <= 0.01123596: F3 (2.5)
: : ALT.4 > 0.01123596:
: : :...Age <= 0.06896552:
: : :...Plat <= 0.4511169: F1 (3.5)
: : : Plat > 0.4511169: F3 (2.6/1.1)
: : Age > 0.06896552:
: : :...RNA.4 <= 0.786327:
: : :...RBC > 0.4832055: F4 (14.1/0.5)
: : : RBC <= 0.4832055:
: : : :...ALT.1 <= 0.3932584: F2 (5.6/1.5)
: : : ALT.1 > 0.3932584: F4 (7.6/2)
: : RNA.4 > 0.786327:
: : :...AST.1 > 0.8988764: F2 (3.3)
: : AST.1 <= 0.8988764:
: : :...RNA.4 <= 0.8668897: F3 (2.8)
: : RNA.4 > 0.8668897: F4 (4.5)
: ALT.4 > 0.4831461:
: :...ALT.24 <= 0.1460674:
: :...ALT.1 > 0.4382023: F4 (7.9/1.8)
: : ALT.1 <= 0.4382023:
: : :...Plat <= 0.4948033: F1 (4.7)
: : Plat > 0.4948033: F3 (2.9/0.6)
: ALT.24 > 0.1460674:
: :...AST.1 <= 0.1573034:
: :...ALT.4 <= 0.5280899: F1 (3.5/1.2)
: : ALT.4 > 0.5280899:
: : :...ALT.after.24.w <= 0.7391304: F4 (4.4/1.1)
: : ALT.after.24.w > 0.7391304: F3 (2/0.2)
: AST.1 > 0.1573034:
: :...ALT.24 > 0.8539326:
: :...BMI <= 0.6153846:
: : :...RNA.Base <= 0.2386587: F2 (2.9)
: : : RNA.Base > 0.2386587: F4 (3)
: : BMI > 0.6153846:
: : :...RNA.Base <= 0.1556014: F3 (2.4/0.6)
: : RNA.Base > 0.1556014: F2 (5.4/0.7)
: ALT.24 <= 0.8539326:
: :...AST.1 <= 0.2921348:
: :...ALT.48 > 0.8876405: F1 (2.4)
: : ALT.48 <= 0.8876405:
: : :...Age <= 0.5862069: F2 (8.7)
: : Age > 0.5862069: F3 (3/0.8)
: AST.1 > 0.2921348:
: :...RNA.4 <= 0.09503957: F1 (4.3/0.4)
: RNA.4 > 0.09503957:
: :...ALT.12 > 0.8876405: F3 (3.6)
: ALT.12 <= 0.8876405:
: :...Plat > 0.6820256:
: :...ALT.4 <= 0.6067415: F1 (2.2/0.6)
: : ALT.4 > 0.6067415: F2 (7.5/1)
: Plat <= 0.6820256:
: :...ALT.48 <= 0.1573034: F3 (6.8/1.1)
: ALT.48 > 0.1573034:
: :...Plat <= 0.1658811:
: :...Plat <= 0.1174064: F1 (5.3/1.7)
: : Plat > 0.1174064: F2 (4/0.4)
: Plat > 0.1658811: [S6]
ALT.after.24.w <= 0.4347826:
:...ALT.4 <= 0.06741573:
:...ALT.after.24.w > 0.3478261: F3 (4.2/1.9)
: ALT.after.24.w <= 0.3478261:
: :...ALT.48 <= 0.7865168: F1 (13/2.1)
: ALT.48 > 0.7865168: F4 (2.5/1)
ALT.4 > 0.06741573:
:...Plat > 0.9282733:
:...ALT.24 <= 0.741573: F2 (4.8)
: ALT.24 > 0.741573: F4 (4.2)
Plat <= 0.9282733:
:...ALT.12 > 0.7752809:
:...BMI > 0.9230769: F1 (4.8/0.8)
: BMI <= 0.9230769:
: :...RNA.Base > 0.8397835: F2 (6.4/0.7)
: RNA.Base <= 0.8397835:
: :...ALT.12 > 0.9213483: F3 (5.9)
: ALT.12 <= 0.9213483:
: :...RNA.Base > 0.542564: F2 (4.9/0.5)
: RNA.Base <= 0.542564:
: :...ALT.24 <= 0.494382: F3 (6.9)
: ALT.24 > 0.494382:
: :...RNA.Base <= 0.3638107: F2 (5.6/1)
: RNA.Base > 0.3638107: F3 (2.7)
ALT.12 <= 0.7752809:
:...RNA.Base > 0.9534334:
:...ALT.48 <= 0.2921348: F1 (3.7)
: ALT.48 > 0.2921348: F2 (4)
RNA.Base <= 0.9534334:
:...RNA.Base > 0.8711762:
:...ALT.36 <= 0.505618: F4 (5)
: ALT.36 > 0.505618:
: :...BMI <= 0.6923077: F4 (3.6/0.6)
: BMI > 0.6923077: F3 (4)
RNA.Base <= 0.8711762:
:...ALT.1 <= 0.1011236:
:...ALT.24 > 0.988764: F2 (3.3)
: ALT.24 <= 0.988764:
: :...ALT.4 <= 0.2247191: F2 (2.6)
: ALT.4 > 0.2247191:
: :...ALT.24 <= 0.9438202: F3 (11.2/2.8)
: ALT.24 > 0.9438202: F1 (2.7)
ALT.1 > 0.1011236:
:...ALT.1 <= 0.1910112:
:...WBC <= 0.4117453: F4 (2.3/0.7)
: WBC > 0.4117453: F2 (5.7)
ALT.1 > 0.1910112:
:...ALT.1 <= 0.3033708:
:...ALT.36 <= 0.1235955: F4 (2.3)
: ALT.36 > 0.1235955:
: :...Plat <= 0.1787922: F1 (2.1)
: Plat > 0.1787922: F3 (10.4/2.6)
ALT.1 > 0.3033708:
:...AST.1 > 0.5617977:
:...Plat > 0.5875865:
: :...ALT.48 <= 0.4606742: F1 (2.4)
: : ALT.48 > 0.4606742: F3 (4.4/1.6)
: Plat <= 0.5875865:
: :...WBC > 0.743798: [S7]
: WBC <= 0.743798: [S8]
AST.1 <= 0.5617977:
:...RNA.Base > 0.6435168: F4 (10.3/4)
RNA.Base <= 0.6435168:
:...ALT.24 <= 0.1123596: F1 (2)
ALT.24 > 0.1123596: [S9]
SubTree [S1]
ALT.36 > 0.8539326: F3 (3.2/1.6)
ALT.36 <= 0.8539326:
:...RNA.Base > 0.4084508: F4 (11.6/0.8)
RNA.Base <= 0.4084508:
:...ALT.after.24.w <= 0.4347826: F3 (6.6/2.1)
ALT.after.24.w > 0.4347826: F4 (3.6/1)
SubTree [S2]
ALT.after.24.w <= 0.4782609: F4 (4.8/1)
ALT.after.24.w > 0.4782609:
:...Plat <= 0.5875865: F3 (6.6/1.3)
Plat > 0.5875865: F4 (4.3)
SubTree [S3]
ALT.36 <= 0.7865168: F4 (16.5/2.3)
ALT.36 > 0.7865168:
:...Plat <= 0.3260598: F3 (3.2)
Plat > 0.3260598: F1 (2.6/1.3)
SubTree [S4]
Age > 0.6206896: F1 (5.4/2.1)
Age <= 0.6206896:
:...Age <= 0.4482759: F1 (3.3)
Age > 0.4482759: F4 (7.9/1.4)
SubTree [S5]
AST.1 > 0.6629214: F1 (2.3)
AST.1 <= 0.6629214:
:...AST.1 <= 0.3595506:
:...ALT.1 <= 0.4044944: F4 (8.5/2.4)
: ALT.1 > 0.4044944: F1 (5.6/1.4)
AST.1 > 0.3595506:
:...Age <= 0.6896552: F2 (3.8)
Age > 0.6896552: F4 (6.4/1.1)
SubTree [S6]
ALT.4 <= 0.6067415: F3 (3.9/1.2)
ALT.4 > 0.6067415: F1 (12.7/2.1)
SubTree [S7]
ALT.24 <= 0.3370787: F4 (5.1)
ALT.24 > 0.3370787: F1 (4.7/2.5)
SubTree [S8]
ALT.1 <= 0.494382: F4 (9.3/1)
ALT.1 > 0.494382:
:...RNA.4 <= 0.1776502: F4 (2.1)
RNA.4 > 0.1776502: F2 (9/0.2)
SubTree [S9]
RNA.4 > 0.9595085: F4 (2.5)
RNA.4 <= 0.9595085:
:...AST.1 <= 0.02247191: F4 (2.1/1)
AST.1 > 0.02247191:
:...Plat <= 0.7179264: F3 (18.4/0.9)
Plat > 0.7179264:
:...Plat <= 0.850447: F2 (3.7)
Plat > 0.850447: F3 (2.3)
----- Trial 9: -----
Decision tree:
BMI <= 0.4615385:
:...RNA.Base > 0.8552055:
: :...AST.1 <= 0.1123596: F4 (9.5/2)
: : AST.1 > 0.1123596:
: : :...Age <= 0.2413793: F1 (9.9/1.4)
: : Age > 0.2413793:
: : :...WBC > 0.8753018: F3 (8.8/2.4)
: : WBC <= 0.8753018:
: : :...ALT.36 > 0.8089887:
: : :...ALT.12 <= 0.4606742: F3 (3/1.4)
: : : ALT.12 > 0.4606742: F1 (6.8/0.9)
: : ALT.36 <= 0.8089887:
: : :...Plat > 0.7116845: F4 (8.4/1.1)
: : Plat <= 0.7116845:
: : :...WBC > 0.7139407: F1 (4.6)
: : WBC <= 0.7139407:
: : :...BMI <= 0.1538462:
: : :...ALT.4 <= 0.6516854: F3 (3.6)
: : : ALT.4 > 0.6516854: F4 (2.2)
: : BMI > 0.1538462:
: : :...Plat > 0.5021918: F3 (2.3/0.8)
: : Plat <= 0.5021918:
: : :...ALT.1 <= 0.8539326: F4 (7.2/1.6)
: : ALT.1 > 0.8539326: F1 (4.4/0.7)
: RNA.Base <= 0.8552055:
: :...ALT.48 <= 0.08988764:
: :...RNA.4 <= 0.4313345:
: : :...ALT.48 > 0.05617978: F4 (4.9/2.4)
: : : ALT.48 <= 0.05617978:
: : : :...ALT.after.24.w <= 0.08695652: F3 (3.5/0.7)
: : : ALT.after.24.w > 0.08695652:
: : : :...ALT.12 <= 0.3707865: F3 (2.1)
: : : ALT.12 > 0.3707865: F4 (12/2.6)
: : RNA.4 > 0.4313345:
: : :...ALT.1 <= 0.2808989:
: : :...ALT.after.24.w <= 0.2608696: F2 (2.5/0.4)
: : : ALT.after.24.w > 0.2608696: F1 (5/0.4)
: : ALT.1 > 0.2808989:
: : :...ALT.12 > 0.6741573: F2 (3.4/1.9)
: : ALT.12 <= 0.6741573:
: : :...ALT.after.24.w <= 0.1304348: F2 (3.1/0.9)
: : ALT.after.24.w > 0.1304348: F4 (13.9/0.8)
: ALT.48 > 0.08988764:
: :...AST.1 > 0.7752809:
: :...RBC > 0.8593162:
: : :...ALT.1 <= 0.6292135: F1 (7.6)
: : : ALT.1 > 0.6292135: F3 (2.8/1)
: : RBC <= 0.8593162:
: : :...RNA.4 > 0.7799128:
: : :...ALT.4 <= 0.4269663: F4 (6.2/2)
: : : ALT.4 > 0.4269663:
: : : :...ALT.24 <= 0.7303371: F3 (5.4)
: : : ALT.24 > 0.7303371: F1 (3/0.4)
: : RNA.4 <= 0.7799128:
: : :...Age <= 0.4827586:
: : :...ALT.36 > 0.8089887: F4 (4.8/2)
: : : ALT.36 <= 0.8089887:
: : : :...RNA.4 <= 0.1971815: F1 (4.4/1.7)
: : : RNA.4 > 0.1971815:
: : : :...ALT.1 > 0.752809: F1 (3.4)
: : : ALT.1 <= 0.752809:
: : : :...ALT.24 <= 0.7752809: F2 (11/1.8)
: : : ALT.24 > 0.7752809: F3 (3.6/1.1)
: : Age > 0.4827586:
: : :...ALT.after.24.w <= 0.173913: F3 (6.1/0.9)
: : ALT.after.24.w > 0.173913:
: : :...ALT.48 > 0.6292135: F2 (9.7/0.3)
: : ALT.48 <= 0.6292135:
: : :...RNA.4 > 0.6257234: F2 (3.1)
: : RNA.4 <= 0.6257234:
: : :...ALT.4 <= 0.3483146: F2 (2.4/0.3)
: : ALT.4 > 0.3483146: F3 (4.6)
: AST.1 <= 0.7752809:
: :...WBC > 0.9231614:
: :...Plat > 0.6754689: F1 (3.1)
: : Plat <= 0.6754689:
: : :...ALT.24 <= 0.1235955: F2 (2.2/0.8)
: : ALT.24 > 0.1235955: F4 (9.7)
: WBC <= 0.9231614:
: :...ALT.24 > 0.7191011:
: :...WBC > 0.8602635: F4 (5.8)
: : WBC <= 0.8602635:
: : :...ALT.after.24.w <= 0.2608696:
: : :...Plat > 0.7688665: F1 (7.4/1.1)
: : : Plat <= 0.7688665:
: : : :...RBC <= 0.5741384: F4 (5.5/0.6)
: : : RBC > 0.5741384:
: : : :...Plat <= 0.6791182: F2 (6.8)
: : : Plat > 0.6791182: F4 (2.5)
: : ALT.after.24.w > 0.2608696:
: : :...ALT.4 > 0.8426966:
: : :...ALT.4 <= 0.988764: F4 (9/0.5)
: : : ALT.4 > 0.988764: F1 (2.3)
: : ALT.4 <= 0.8426966:
: : :...ALT.36 > 0.7640449:
: : :...ALT.after.24.w <= 0.5652174: F1 (3)
: : : ALT.after.24.w > 0.5652174:
: : : :...ALT.1 <= 0.1235955: F1 (2.2)
: : : ALT.1 > 0.1235955: F4 (4.4/0.4)
: : ALT.36 <= 0.7640449:
: : :...Plat > 0.6687773:
: : :...ALT.after.24.w <= 0.5652174: F1 (5.6/0.4)
: : : ALT.after.24.w > 0.5652174: F2 (5.3/1.5)
: : Plat <= 0.6687773:
: : :...RNA.Base <= 0.4190429: F3 (9.5/1.1)
: : RNA.Base > 0.4190429:
: : :...BMI <= 0.3846154: F1 (6.9/0.3)
: : BMI > 0.3846154: F3 (2.5/0.1)
: ALT.24 <= 0.7191011:
: :...WBC <= 0.1418222:
: :...AST.1 > 0.5842696:
: : :...Age <= 0.2758621: F4 (2.7)
: : : Age > 0.2758621: F3 (6.2)
: : AST.1 <= 0.5842696:
: : :...ALT.36 > 0.7078652:
: : :...ALT.36 <= 0.8202247: F3 (2.1)
: : : ALT.36 > 0.8202247: F4 (8.1/1.3)
: : ALT.36 <= 0.7078652:
: : :...AST.1 <= 0.3483146: F2 (11.2/0.9)
: : AST.1 > 0.3483146:
: : :...Age <= 0.4137931: F4 (3.6)
: : Age > 0.4137931: F2 (2.8)
: WBC > 0.1418222:
: :...BMI <= 0.1538462:
: :...ALT.12 > 0.8876405:
: : :...RBC > 0.4552677: F4 (9.2/1.6)
: : : RBC <= 0.4552677:
: : : :...WBC <= 0.5137212: F3 (2.8/0.9)
: : : WBC > 0.5137212: F1 (4.5)
: : ALT.12 <= 0.8876405:
: : :...ALT.after.24.w > 0.9130435: F4 (5.4/2.6)
: : ALT.after.24.w <= 0.9130435:
: : :...ALT.12 <= 0.2022472: F4 (8.2/1.9)
: : ALT.12 > 0.2022472:
: : :...ALT.36 <= 0.4719101:
: : :...ALT.24 > 0.6853933: F3 (2.4/1.1)
: : : ALT.24 <= 0.6853933:
: : : :...Plat <= 0.3180718: F2 (6.1/0.9)
: : : Plat > 0.3180718:
: : : :...RNA.Base <= 0.5729684: F3 (4.8/0.8)
: : : RNA.Base > 0.5729684: F2 (5.8/1)
: : ALT.36 > 0.4719101:
: : :...ALT.24 <= 0.04494382: F3 (3.1/1.5)
: : ALT.24 > 0.04494382:
: : :...RBC > 0.4102663: F4 (9.5/3.8)
: : RBC <= 0.4102663:
: : :...RNA.4 <= 0.3422182: F2 (6.2/0.5)
: : RNA.4 > 0.3422182: F1 (4.9/1)
: BMI > 0.1538462:
: :...ALT.4 > 0.752809:
: :...ALT.12 > 0.5842696: F3 (11.1/1.7)
: : ALT.12 <= 0.5842696:
: : :...ALT.1 > 0.7752809: F1 (7.9/1.1)
: : ALT.1 <= 0.7752809:
: : :...ALT.after.24.w <= 0.6086956: F1 (5.7/1.6)
: : ALT.after.24.w > 0.6086956: F3 (6.3)
: ALT.4 <= 0.752809:
: :...ALT.12 <= 0.1460674:
: :...ALT.36 <= 0.7865168: F3 (9.4/1.4)
: : ALT.36 > 0.7865168: F1 (4.1/1.2)
: ALT.12 > 0.1460674:
: :...ALT.after.24.w > 0.6956522:
: :...RNA.Base <= 0.0462494: F3 (2.7)
: : RNA.Base > 0.0462494: F2 (9.1/1.2)
: ALT.after.24.w <= 0.6956522:
: :...ALT.36 > 0.7640449:
: :...ALT.4 <= 0.1910112: F2 (2.3/0.5)
: : ALT.4 > 0.1910112: F3 (5/0.9)
: ALT.36 <= 0.7640449:
: :...BMI > 0.3846154: F4 (7.2/1.6)
: BMI <= 0.3846154:
: :...Age <= 0.3448276: F1 (4/0.8)
: Age > 0.3448276:
: :...ALT.4 <= 0.08988764: F2 (3/1)
: ALT.4 > 0.08988764: [S1]
BMI > 0.4615385:
:...ALT.1 <= 0.01123596: F2 (12.9/2.9)
ALT.1 > 0.01123596:
:...ALT.1 > 0.8426966:
:...AST.1 <= 0.06741573: F3 (5.1/0.6)
: AST.1 > 0.06741573:
: :...RNA.4 <= 0.1141998:
: :...Age > 0.4827586: F1 (9.7/1.6)
: : Age <= 0.4827586:
: : :...Age <= 0.2758621: F1 (3/1.5)
: : Age > 0.2758621: F4 (2.9)
: RNA.4 > 0.1141998:
: :...RBC <= 0.2015534: F3 (8.3/1.9)
: RBC > 0.2015534:
: :...Plat <= 0.3180718:
: :...ALT.4 <= 0.2808989: F3 (2.8/1)
: : ALT.4 > 0.2808989: F2 (11.2/1.2)
: Plat > 0.3180718:
: :...ALT.48 <= 0.1573034: F3 (2.4)
: ALT.48 > 0.1573034:
: :...ALT.4 > 0.752809: F1 (8.3/0.3)
: ALT.4 <= 0.752809:
: :...ALT.after.24.w > 0.6956522:
: :...BMI <= 0.7692308: F2 (2.7/0.6)
: : BMI > 0.7692308: F4 (3.8)
: ALT.after.24.w <= 0.6956522:
: :...WBC > 0.6770582: F2 (3.4/0.6)
: WBC <= 0.6770582:
: :...ALT.after.24.w <= 0.2173913: F1 (5.2/2.2)
: ALT.after.24.w > 0.2173913:
: :...ALT.48 > 0.7191011: F3 (4.5)
: ALT.48 <= 0.7191011:
: :...ALT.1 <= 0.9550562: F1 (4.9)
: ALT.1 > 0.9550562: F3 (3/1.2)
ALT.1 <= 0.8426966:
:...ALT.36 <= 0.01123596:
:...ALT.48 <= 0.8314607: F2 (8.1/1)
: ALT.48 > 0.8314607: F4 (2.5)
ALT.36 > 0.01123596:
:...ALT.1 <= 0.4044944:
:...AST.1 <= 0.1460674:
: :...ALT.48 <= 0.2808989:
: : :...RNA.4 <= 0.4198684: F4 (2.4/1)
: : : RNA.4 > 0.4198684: F1 (7.4)
: : ALT.48 > 0.2808989:
: : :...ALT.24 > 0.8539326: F4 (6.3/2.2)
: : ALT.24 <= 0.8539326:
: : :...ALT.24 <= 0.3258427: F3 (4.7)
: : ALT.24 > 0.3258427:
: : :...WBC <= 0.5068057: F4 (3.8)
: : WBC > 0.5068057: F3 (8/3.2)
: AST.1 > 0.1460674:
: :...ALT.1 > 0.3707865:
: :...BMI > 0.6923077: F1 (5.3)
: : BMI <= 0.6923077:
: : :...RNA.Base <= 0.4595791: F3 (5.6)
: : RNA.Base > 0.4595791: F2 (3/1.3)
: ALT.1 <= 0.3707865:
: :...Plat > 0.9235899: F2 (6.6/1.6)
: Plat <= 0.9235899:
: :...AST.1 > 0.6179775:
: :...ALT.1 > 0.3258427:
: : :...AST.1 <= 0.9662921: F1 (5.4/1.2)
: : : AST.1 > 0.9662921: F2 (2.5/0.4)
: : ALT.1 <= 0.3258427:
: : :...BMI <= 0.6923077:
: : :...Age > 0.7586207: F1 (5.8/1.8)
: : : Age <= 0.7586207:
: : : :...ALT.48 <= 0.4044944: F4 (8/0.5)
: : : ALT.48 > 0.4044944: F3 (6.5/1.4)
: : BMI > 0.6923077:
: : :...ALT.24 > 0.7752809:
: : :...RNA.4 <= 0.3898644: F1 (5/2)
: : : RNA.4 > 0.3898644: [S2]
: : ALT.24 <= 0.7752809:
: : :...WBC <= 0.2644347: F1 (3.9)
: : WBC > 0.2644347: [S3]
: AST.1 <= 0.6179775:
: :...Plat <= 0.03680752: F1 (5.6/2.2)
: Plat > 0.03680752:
: :...Age <= 0.03448276: F4 (2.9/0.9)
: Age > 0.03448276:
: :...BMI <= 0.5384616: F3 (4.4/1.6)
: BMI > 0.5384616:
: :...RNA.Base > 0.8823329:
: :...BMI <= 0.6923077: F1 (4.1/1.4)
: : BMI > 0.6923077: F4 (4.2/1.4)
: RNA.Base <= 0.8823329:
: :...RNA.Base <= 0.282621:
: :...BMI <= 0.6153846: F1 (3/1.9)
: : BMI > 0.6153846: [S4]
: RNA.Base > 0.282621:
: :...WBC <= 0.3552141: F2 (7.1/1.7)
: WBC > 0.3552141:
: :...RBC > 0.681234: F3 (4.1)
: RBC <= 0.681234: [S5]
ALT.1 > 0.4044944:
:...ALT.1 <= 0.494382:
:...RNA.4 > 0.8748442:
: :...WBC <= 0.1738749: F3 (3.1/0.1)
: : WBC > 0.1738749: F2 (4)
: RNA.4 <= 0.8748442:
: :...AST.1 <= 0.1348315: F2 (3.3)
: AST.1 > 0.1348315:
: :...ALT.36 <= 0.08988764: F3 (2.3)
: ALT.36 > 0.08988764:
: :...ALT.4 <= 0.752809: F4 (22.3/3.1)
: ALT.4 > 0.752809:
: :...ALT.36 <= 0.4269663: F4 (2.8/0.1)
: ALT.36 > 0.4269663: F2 (4.4/1.4)
ALT.1 > 0.494382:
:...ALT.4 <= 0.02247191: F2 (4.7)
ALT.4 > 0.02247191:
:...ALT.48 <= 0.08988764:
:...ALT.1 <= 0.6067415: F1 (5.8)
: ALT.1 > 0.6067415: F3 (5.6/3.1)
ALT.48 > 0.08988764:
:...ALT.36 > 0.8314607:
:...WBC <= 0.4554336: F3 (6.3/3.2)
: WBC > 0.4554336: F2 (13.7/1.3)
ALT.36 <= 0.8314607:
:...ALT.4 > 0.9213483: F2 (3.1)
ALT.4 <= 0.9213483:
:...ALT.after.24.w > 0.5217391:
:...ALT.24 <= 0.04494382: F2 (5.1/1.6)
: ALT.24 > 0.04494382:
: :...ALT.48 <= 0.2134831: F4 (8.7/1.9)
: ALT.48 > 0.2134831:
: :...ALT.4 <= 0.3370787:
: :...RBC <= 0.2451413: F1 (5.5/3.1)
: : RBC > 0.2451413:
: : :...Age <= 0.6206896: F4 (8.5/1)
: : Age > 0.6206896: F1 (2.3/1)
: ALT.4 > 0.3370787:
: :...RBC <= 0.1417537: F4 (3.8)
: RBC > 0.1417537:
: :...ALT.24 <= 0.2921348: [S6]
: ALT.24 > 0.2921348: [S7]
ALT.after.24.w <= 0.5217391:
:...RNA.Base > 0.7515293:
:...ALT.24 > 0.752809: F4 (2.6)
: ALT.24 <= 0.752809:
: :...Age <= 0.2758621: F2 (2.5)
: Age > 0.2758621: F1 (4.7/1)
RNA.Base <= 0.7515293:
:...ALT.1 > 0.8314607: F2 (2.9)
ALT.1 <= 0.8314607:
:...BMI <= 0.5384616:
:...ALT.48 <= 0.3707865: F2 (4.5/1.1)
: ALT.48 > 0.3707865: F3 (3.4)
BMI > 0.5384616:
:...ALT.36 <= 0.1123596: F1 (5.4/3.5)
ALT.36 > 0.1123596: [S8]
SubTree [S1]
ALT.48 <= 0.247191: F2 (2.6)
ALT.48 > 0.247191:
:...RNA.Base <= 0.3271777: F2 (4.6/1.9)
RNA.Base > 0.3271777: F4 (9.9/1.9)
SubTree [S2]
ALT.after.24.w <= 0.4782609: F3 (2.9)
ALT.after.24.w > 0.4782609: F2 (3.5/0.8)
SubTree [S3]
ALT.after.24.w <= 0.08695652: F1 (2.9)
ALT.after.24.w > 0.08695652:
:...ALT.48 <= 0.8089887: F3 (8.5/1.7)
ALT.48 > 0.8089887: F4 (2.4/0.6)
SubTree [S4]
AST.1 <= 0.5280899: F2 (7.9/1.6)
AST.1 > 0.5280899: F1 (3.2)
SubTree [S5]
RBC > 0.5397249: F2 (4.9)
RBC <= 0.5397249:
:...ALT.4 <= 0.5168539: F2 (2.6)
ALT.4 > 0.5168539: F3 (5.9/0.7)
SubTree [S6]
RNA.Base <= 0.3773303: F4 (4.3/0.5)
RNA.Base > 0.3773303: F3 (3.7/0.5)
SubTree [S7]
Plat <= 0.1632135: F2 (2.4)
Plat > 0.1632135: F3 (13.6/1.5)
SubTree [S8]
ALT.24 > 0.6067415: F3 (14.4/0.6)
ALT.24 <= 0.6067415:
:...ALT.36 > 0.5730337: F3 (4.9)
ALT.36 <= 0.5730337:
:...Age > 0.7931035: F2 (2.9/1.4)
Age <= 0.7931035:
:...ALT.48 <= 0.7640449: F1 (4/0.6)
ALT.48 > 0.7640449: F4 (3.9/1)
----- Trial 10: -----
Decision tree:
ALT.after.24.w > 0.7826087:
:...ALT.36 > 0.8764045:
: :...RBC <= 0.2340792: F1 (3.9/1)
: : RBC > 0.2340792:
: : :...WBC <= 0.3826564: F4 (6.3/1.4)
: : WBC > 0.3826564:
: : :...AST.1 <= 0.247191: F4 (2.8)
: : AST.1 > 0.247191: F2 (7.7/2)
: ALT.36 <= 0.8764045:
: :...ALT.24 <= 0.04494382:
: :...ALT.1 <= 0.7752809: F1 (6.4)
: : ALT.1 > 0.7752809: F3 (3.4/0.5)
: ALT.24 > 0.04494382:
: :...AST.1 <= 0.1348315:
: :...ALT.48 <= 0.2808989: F1 (8.9/1.1)
: : ALT.48 > 0.2808989:
: : :...Age > 0.7241379: F1 (5.7/1.6)
: : Age <= 0.7241379:
: : :...AST.1 > 0.06741573: F3 (4.6/0.7)
: : AST.1 <= 0.06741573:
: : :...ALT.24 <= 0.247191: F3 (2.3)
: : ALT.24 > 0.247191: F4 (9.1/1.5)
: AST.1 > 0.1348315:
: :...ALT.12 > 0.8876405:
: :...AST.1 > 0.6629214: F3 (2.5)
: : AST.1 <= 0.6629214:
: : :...ALT.36 <= 0.2022472: F3 (4.2/1.5)
: : ALT.36 > 0.2022472: F4 (7)
: ALT.12 <= 0.8876405:
: :...WBC <= 0.033809: F3 (5.1)
: WBC > 0.033809:
: :...RBC > 0.9085496: F4 (7.7/1.5)
: RBC <= 0.9085496:
: :...ALT.12 > 0.6741573:
: :...Plat > 0.7382635:
: : :...Age <= 0.6551724: F3 (4.9)
: : : Age > 0.6551724: F1 (4)
: : Plat <= 0.7382635:
: : :...WBC > 0.456202: F1 (7.9)
: : WBC <= 0.456202:
: : :...RNA.Base <= 0.6670924: F2 (2.9)
: : RNA.Base > 0.6670924: F1 (3.8/1.3)
: ALT.12 <= 0.6741573:
: :...RBC <= 0.4371808:
: :...ALT.24 > 0.6966292: F4 (10.8/2.2)
: : ALT.24 <= 0.6966292:
: : :...RBC <= 0.06872547: F3 (5.6/0.8)
: : RBC > 0.06872547:
: : :...RNA.4 > 0.5562931:
: : :...RNA.4 <= 0.8958376: F4 (7.4/0.9)
: : : RNA.4 > 0.8958376: F2 (5.7)
: : RNA.4 <= 0.5562931:
: : :...BMI <= 0.3846154: F2 (10.2/1.6)
: : BMI > 0.3846154:
: : :...ALT.12 <= 0.06741573: F2 (2.8/1.1)
: : ALT.12 > 0.06741573:
: : :...AST.1 <= 0.8651685: F1 (4.2/0.9)
: : AST.1 > 0.8651685: F3 (2)
: RBC > 0.4371808:
: :...ALT.1 > 0.7977528:
: :...Plat <= 0.120089: F2 (2.1)
: : Plat > 0.120089: F1 (7.7/0.6)
: ALT.1 <= 0.7977528:
: :...ALT.1 <= 0: F2 (2.6)
: ALT.1 > 0:
: :...Age <= 0.4137931:
: :...ALT.48 <= 0.505618:
: : :...RNA.Base <= 0.4448915: F1 (5.4)
: : : RNA.Base > 0.4448915: F3 (3.4/0.8)
: : ALT.48 > 0.505618:
: : :...BMI <= 0: F1 (2.3/0.6)
: : BMI > 0:
: : :...ALT.48 <= 0.7865168: F4 (5.2/0.8)
: : ALT.48 > 0.7865168: F3 (2.6)
: Age > 0.4137931:
: :...ALT.36 <= 0.1011236: F1 (2.6/0.9)
: ALT.36 > 0.1011236:
: :...BMI > 0.9230769: F2 (4.2/2)
: BMI <= 0.9230769:
: :...ALT.1 > 0.5955056: F3 (8.8/0.9)
: ALT.1 <= 0.5955056: [S1]
ALT.after.24.w <= 0.7826087:
:...ALT.36 <= 0.01123596:
:...WBC <= 0.6020856:
: :...ALT.4 <= 0.9101124: F2 (10/1.5)
: : ALT.4 > 0.9101124: F4 (2.1)
: WBC > 0.6020856:
: :...AST.1 <= 0.1348315: F2 (2.1)
: AST.1 > 0.1348315: F1 (5.9/0.8)
ALT.36 > 0.01123596:
:...ALT.after.24.w > 0.6956522:
:...RBC > 0.9511334:
: :...ALT.1 <= 0.8426966: F2 (6/0.8)
: : ALT.1 > 0.8426966: F3 (2.1)
: RBC <= 0.9511334:
: :...ALT.48 <= 0.3033708:
: :...ALT.36 <= 0.3033708: F4 (9.3)
: : ALT.36 > 0.3033708:
: : :...RNA.4 <= 0.4014155: F1 (4/0.4)
: : RNA.4 > 0.4014155: F3 (5.3/2.3)
: ALT.48 > 0.3033708:
: :...ALT.1 > 0.8651685: F2 (5.5)
: ALT.1 <= 0.8651685:
: :...ALT.4 > 0.3820225:
: :...ALT.48 <= 0.3370787: F2 (3.5)
: : ALT.48 > 0.3370787: F4 (17.8/5.6)
: ALT.4 <= 0.3820225:
: :...AST.1 <= 0.2359551: F2 (4.3)
: AST.1 > 0.2359551:
: :...Plat <= 0.2732014: F4 (2)
: Plat > 0.2732014:
: :...ALT.12 > 0.741573: F1 (4.8/1.9)
: ALT.12 <= 0.741573:
: :...Plat <= 0.6354542: F2 (4.3)
: Plat > 0.6354542: F1 (4.6/0.8)
ALT.after.24.w <= 0.6956522:
:...ALT.4 > 0.9213483:
:...Plat <= 0.1090887: F4 (3.9/1.1)
: Plat > 0.1090887:
: :...ALT.1 > 0.9213483: F3 (3.4/1.1)
: ALT.1 <= 0.9213483:
: :...ALT.12 <= 0.1348315: F4 (2.2/0.3)
: ALT.12 > 0.1348315:
: :...RBC <= 0.5517238: F1 (15/4.6)
: RBC > 0.5517238:
: :...ALT.12 <= 0.3707865: F1 (4.3)
: ALT.12 > 0.3707865: F2 (12.1)
ALT.4 <= 0.9213483:
:...BMI > 0.4615385:
:...WBC <= 0.09363337:
: :...Plat > 0.7792973:
: : :...Plat <= 0.8763666: F3 (4.7)
: : : Plat > 0.8763666: F1 (5.3/1.7)
: : Plat <= 0.7792973:
: : :...ALT.48 > 0.7865168: F3 (2.2/0.6)
: : ALT.48 <= 0.7865168:
: : :...ALT.12 <= 0.3258427: F1 (4.1)
: : ALT.12 > 0.3258427:
: : :...Age <= 0.03448276: F1 (2.2)
: : Age > 0.03448276: F2 (13.6/0.3)
: WBC > 0.09363337:
: :...Plat > 0.9667069: F2 (8/0.8)
: Plat <= 0.9667069:
: :...ALT.36 <= 0.05617978:
: :...ALT.48 <= 0.2247191: F3 (4.7)
: : ALT.48 > 0.2247191: F4 (12.1/3.6)
: ALT.36 > 0.05617978:
: :...ALT.1 <= 0.1011236:
: :...ALT.1 > 0.04494382:
: : :...ALT.48 <= 0.4157303: F1 (9.6/1.3)
: : : ALT.48 > 0.4157303: F3 (3.7)
: : ALT.1 <= 0.04494382:
: : :...ALT.48 <= 0.1123596: F3 (3.5/1.1)
: : ALT.48 > 0.1123596:
: : :...Age <= 0.3103448: F1 (3.1)
: : Age > 0.3103448: F2 (7.2/2)
: ALT.1 > 0.1011236:
: :...AST.1 > 0.9550562:
: :...AST.1 <= 0.988764: F2 (2.6)
: : AST.1 > 0.988764: F4 (6.5/2)
: AST.1 <= 0.9550562:
: :...ALT.1 > 0.6966292:
: :...ALT.1 <= 0.741573:
: : :...ALT.1 <= 0.7303371: F3 (7.1/2.2)
: : : ALT.1 > 0.7303371: F4 (6.6/0.5)
: : ALT.1 > 0.741573:
: : :...RNA.Base <= 0.05632871: F2 (5.8/1.8)
: : RNA.Base > 0.05632871:
: : :...ALT.48 > 0.9550562: F1 (5.3)
: : ALT.48 <= 0.9550562:
: : :...WBC <= 0.4050494:
: : :...Age > 0.4482759: [S2]
: : : Age <= 0.4482759: [S3]
: : WBC > 0.4050494:
: : :...ALT.24 <= 0.4044944: [S4]
: : ALT.24 > 0.4044944: [S5]
: ALT.1 <= 0.6966292:
: :...ALT.1 > 0.6516854: F2 (9/0.9)
: ALT.1 <= 0.6516854:
: :...ALT.1 > 0.5280899: [S6]
: ALT.1 <= 0.5280899:
: :...RNA.Base <= 0.4039906:
: :...Age > 0.6896552:
: : :...Age > 0.862069: F3 (4/1.1)
: : : Age <= 0.862069: [S7]
: : Age <= 0.6896552:
: : :...WBC > 0.6045005: [S8]
: : WBC <= 0.6045005: [S9]
: RNA.Base > 0.4039906:
: :...RNA.4 <= 0.1684916: [S10]
: RNA.4 > 0.1684916:
: :...BMI <= 0.8461539:
: :...AST.1 <= 0.6853933: [S11]
: : AST.1 > 0.6853933: [S12]
: BMI > 0.8461539:
: :...ALT.24 > 0.741573: [S13]
: ALT.24 <= 0.741573: [S14]
BMI <= 0.4615385:
:...ALT.after.24.w <= 0.08695652:
:...WBC <= 0.2001098:
: :...Plat <= 0.7465287: F2 (9.8/0.6)
: : Plat > 0.7465287: F4 (2)
: WBC > 0.2001098:
: :...RBC <= 0.3884507: F3 (10.2/3.4)
: RBC > 0.3884507:
: :...WBC <= 0.2859495: F1 (7.8/1.8)
: WBC > 0.2859495:
: :...RNA.Base <= 0.5349574: F2 (12.5/2)
: RNA.Base > 0.5349574:
: :...ALT.36 <= 0.8314607: F4 (10.8/3.3)
: ALT.36 > 0.8314607: F1 (2.7/0.8)
ALT.after.24.w > 0.08695652:
:...ALT.12 <= 0.03370786:
:...RNA.Base <= 0.3073422: F1 (2.4/1.1)
: RNA.Base > 0.3073422: F3 (8.8/1)
ALT.12 > 0.03370786:
:...Age <= 0.1034483:
:...RNA.4 > 0.9067978: F1 (4.1)
: RNA.4 <= 0.9067978:
: :...ALT.48 <= 0.1910112:
: :...ALT.36 <= 0.3820225: F1 (2.1)
: : ALT.36 > 0.3820225: F4 (6.9)
: ALT.48 > 0.1910112:
: :...Plat > 0.7162554: F1 (6.8/1.5)
: Plat <= 0.7162554:
: :...RBC <= 0.4274855: F3 (6.8/0.9)
: RBC > 0.4274855: F4 (2.9)
Age > 0.1034483:
:...ALT.24 <= 0.1011236:
:...RNA.4 <= 0.4283188: F3 (9/2.7)
: RNA.4 > 0.4283188:
: :...ALT.4 <= 0.1573034: F4 (5.8/1.6)
: ALT.4 > 0.1573034:
: :...ALT.36 <= 0.5505618: F3 (3.1/0.8)
: ALT.36 > 0.5505618: F2 (5.6)
ALT.24 > 0.1011236:
:...ALT.36 > 0.9662921:
:...AST.1 <= 0.6741573: F2 (2.8/0.3)
: AST.1 > 0.6741573: F3 (4.5)
ALT.36 <= 0.9662921:
:...AST.1 > 0.9438202: F3 (5.5/2.4)
AST.1 <= 0.9438202:
:...Plat <= 0.05252864:
:...ALT.48 > 0.8539326: F4 (2.8)
: ALT.48 <= 0.8539326:
: :...Plat <= 0.01674772: F3 (2.6)
: Plat > 0.01674772: F2 (6.5/0.6)
Plat > 0.05252864:
:...ALT.after.24.w <= 0.2173913: [S15]
ALT.after.24.w > 0.2173913:
:...RNA.4 > 0.7370139:
:...ALT.24 <= 0.4831461: [S16]
: ALT.24 > 0.4831461: [S17]
RNA.4 <= 0.7370139: [S18]
SubTree [S1]
ALT.12 <= 0.3483146: F3 (5.7/1)
ALT.12 > 0.3483146: F4 (3.8)
SubTree [S2]
Plat <= 0.6232025: F4 (3.7)
Plat > 0.6232025: F1 (6.3/1.3)
SubTree [S3]
RNA.Base > 0.7378607: F4 (5.4)
RNA.Base <= 0.7378607:
:...RBC <= 0.2128093: F4 (2.2)
RBC > 0.2128093: F3 (3.7)
SubTree [S4]
Plat <= 0.5613671: F4 (7.4/2.1)
Plat > 0.5613671: F2 (3.7/1.5)
SubTree [S5]
ALT.1 > 0.8539326: F1 (9.7/2.5)
ALT.1 <= 0.8539326:
:...ALT.12 <= 0.7640449: F3 (5.5)
ALT.12 > 0.7640449: F2 (2.9/0.7)
SubTree [S6]
ALT.after.24.w <= 0.5652174: F3 (21.9/5.7)
ALT.after.24.w > 0.5652174: F1 (2.8/1.3)
SubTree [S7]
ALT.4 <= 0.7865168: F1 (3)
ALT.4 > 0.7865168: F2 (3.1)
SubTree [S8]
BMI <= 0.7692308: F3 (7.5/0.3)
BMI > 0.7692308: F1 (3.3/1.3)
SubTree [S9]
RNA.Base > 0.3474912: F1 (4.7)
RNA.Base <= 0.3474912:
:...WBC <= 0.1924259: F1 (2.3/0.7)
WBC > 0.1924259: F4 (9.2/1.7)
SubTree [S10]
ALT.12 <= 0.3820225: F4 (2.6/0.6)
ALT.12 > 0.3820225: F3 (4.1/1.1)
SubTree [S11]
ALT.24 <= 0.9662921: F2 (31.8/9.3)
ALT.24 > 0.9662921: F4 (2.1)
SubTree [S12]
ALT.48 <= 0.494382: F2 (3.3/0.8)
ALT.48 > 0.494382: F3 (4.2)
SubTree [S13]
Plat <= 0.4113645: F2 (5.2/0.8)
Plat > 0.4113645: F1 (3.3)
SubTree [S14]
WBC > 0.617124: F4 (6.1/1.9)
WBC <= 0.617124:
:...ALT.4 <= 0.6629214: F3 (4.8/0.4)
ALT.4 > 0.6629214: F4 (2.1)
SubTree [S15]
ALT.after.24.w > 0.173913: F2 (3/0.4)
ALT.after.24.w <= 0.173913:
:...RBC <= 0.2730283: F1 (5.4/0.7)
RBC > 0.2730283: F4 (19.2/7.8)
SubTree [S16]
RNA.Base <= 0.3852199: F1 (2.6/0.6)
RNA.Base > 0.3852199: F4 (5.6)
SubTree [S17]
ALT.after.24.w > 0.4782609:
:...ALT.48 <= 0.7640449: F3 (15.6/2.3)
: ALT.48 > 0.7640449: F1 (2.3/0.6)
ALT.after.24.w <= 0.4782609:
:...ALT.after.24.w <= 0.3043478: F3 (3.8/0.8)
ALT.after.24.w > 0.3043478:
:...ALT.24 <= 0.7640449: F1 (4.8/1)
ALT.24 > 0.7640449: F4 (2.4)
SubTree [S18]
ALT.after.24.w <= 0.2608696: F1 (4.7)
ALT.after.24.w > 0.2608696:
:...RNA.4 <= 0.07730234:
:...WBC <= 0.1778266: F3 (2.3)
: WBC > 0.1778266: F4 (5.8/0.5)
RNA.4 > 0.07730234:
:...AST.1 > 0.6404495:
:...BMI <= 0.1538462:
: :...ALT.24 <= 0.6966292: F2 (9.2/1.5)
: : ALT.24 > 0.6966292: F3 (3.9/1.6)
: BMI > 0.1538462:
: :...ALT.4 <= 0.3033708: F3 (2.3)
: ALT.4 > 0.3033708:
: :...ALT.24 <= 0.3932584: F4 (4.3/0.9)
: ALT.24 > 0.3932584: F1 (5.6/1.3)
AST.1 <= 0.6404495:
:...WBC <= 0.2018661:
:...Plat <= 0.7792973: F1 (11.2/1.9)
: Plat > 0.7792973: F3 (2.5)
WBC > 0.2018661:
:...ALT.48 <= 0.2022472:
:...AST.1 <= 0.3707865: F2 (3.2/0.6)
: AST.1 > 0.3707865: F4 (6.1)
ALT.48 > 0.2022472:
:...ALT.1 <= 0.2921348: F1 (4.3/2.1)
ALT.1 > 0.2921348:
:...ALT.after.24.w > 0.5217391:
:...ALT.4 <= 0.2134831: F2 (3.2)
: ALT.4 > 0.2134831: F1 (7.3/1.6)
ALT.after.24.w <= 0.5217391:
:...Age > 0.8275862: F1 (4/0.6)
Age <= 0.8275862:
:...ALT.36 <= 0.8764045: F4 (15.2/3.6)
ALT.36 > 0.8764045: F1 (3.3)
----- Trial 11: -----
Decision tree:
ALT.12 > 0.8876405:
:...AST.1 <= 0.06741573:
: :...ALT.48 <= 0.3146068: F1 (2.8/0.5)
: : ALT.48 > 0.3146068: F3 (8.6/0.5)
: AST.1 > 0.06741573:
: :...BMI > 0.7692308:
: :...ALT.after.24.w <= 0.4782609:
: : :...Age <= 0.8965517: F1 (12.7/1.7)
: : : Age > 0.8965517: F2 (3)
: : ALT.after.24.w > 0.4782609:
: : :...ALT.1 <= 0.6516854: F2 (4.7/0.7)
: : ALT.1 > 0.6516854: F4 (3.6/0.6)
: BMI <= 0.7692308:
: :...Age > 0.6206896:
: :...ALT.1 > 0.9550562: F2 (3.4/1.2)
: : ALT.1 <= 0.9550562:
: : :...ALT.after.24.w <= 0.173913: F3 (5.5)
: : ALT.after.24.w > 0.173913:
: : :...ALT.after.24.w <= 0.5652174: F1 (6/1)
: : ALT.after.24.w > 0.5652174: F3 (3.7/1.3)
: Age <= 0.6206896:
: :...RBC <= 0.173995: F1 (8.6/1.7)
: RBC > 0.173995:
: :...ALT.24 <= 0.05617978: F1 (3.9)
: ALT.24 > 0.05617978:
: :...ALT.after.24.w > 0.7826087: F4 (10/2.6)
: ALT.after.24.w <= 0.7826087:
: :...RNA.Base <= 0.2202335: F4 (12.2/2)
: RNA.Base > 0.2202335:
: :...WBC > 0.7675082: F4 (5.4/0.8)
: WBC <= 0.7675082:
: :...AST.1 <= 0.1910112: F2 (3/0.6)
: AST.1 > 0.1910112:
: :...AST.1 > 0.8988764: F2 (3.3/0.5)
: AST.1 <= 0.8988764:
: :...RBC <= 0.3686841: F3 (2.1)
: RBC > 0.3686841: F1 (8.2/1.1)
ALT.12 <= 0.8876405:
:...ALT.36 <= 0.08988764:
:...Age > 0.9310345:
: :...RNA.4 <= 0.7286625: F1 (2.8)
: : RNA.4 > 0.7286625: F2 (3.3/1)
: Age <= 0.9310345:
: :...ALT.48 > 0.7865168:
: :...ALT.36 <= 0.05617978: F4 (9.9/0.5)
: : ALT.36 > 0.05617978: F2 (5.6/0.7)
: ALT.48 <= 0.7865168:
: :...ALT.36 <= 0:
: :...Age > 0.4827586: F4 (2.4)
: : Age <= 0.4827586:
: : :...BMI <= 0.5384616: F1 (2.6)
: : BMI > 0.5384616: F2 (3.8)
: ALT.36 > 0:
: :...ALT.12 > 0.4382023:
: :...AST.1 > 0.505618: F4 (12.3/3.9)
: : AST.1 <= 0.505618:
: : :...ALT.24 <= 0.7977528: F2 (10.1/2.1)
: : ALT.24 > 0.7977528: F4 (2.2)
: ALT.12 <= 0.4382023:
: :...RNA.Base <= 0.3681011:
: :...ALT.48 <= 0.5168539: F2 (6.6/1.4)
: : ALT.48 > 0.5168539: F1 (3.2)
: RNA.Base > 0.3681011:
: :...ALT.after.24.w <= 0.04347826: F2 (2)
: ALT.after.24.w > 0.04347826:
: :...AST.1 > 0.3258427:
: :...ALT.4 <= 0.8426966: F3 (15.4/1.6)
: : ALT.4 > 0.8426966: F1 (2)
: AST.1 <= 0.3258427:
: :...ALT.24 > 0.6179775: F4 (3.9)
: ALT.24 <= 0.6179775:
: :...Plat <= 0.5640197: F3 (2.8)
: Plat > 0.5640197: F2 (3.5/1.1)
ALT.36 > 0.08988764:
:...Age <= 0.137931:
:...RBC <= 0.1387412:
: :...Age > 0.1034483: F2 (5/1.5)
: : Age <= 0.1034483:
: : :...ALT.1 <= 0.4494382: F1 (7.1)
: : ALT.1 > 0.4494382: F4 (5.9/1.5)
: RBC > 0.1387412:
: :...BMI <= 0.3846154:
: :...ALT.36 <= 0.2921348:
: : :...Plat <= 0.4001019: F1 (7/2.9)
: : : Plat > 0.4001019: F3 (3.3)
: : ALT.36 > 0.2921348:
: : :...BMI <= 0.07692308:
: : :...BMI <= 0: F1 (2.6/0.7)
: : : BMI > 0: F3 (4.9/2.1)
: : BMI > 0.07692308:
: : :...Age <= 0: F4 (4.4)
: : Age > 0:
: : :...Age <= 0.1034483: F1 (16.5/5.4)
: : Age > 0.1034483: F4 (3.6/0.4)
: BMI > 0.3846154:
: :...ALT.48 <= 0.1685393:
: :...RNA.Base <= 0.7343804: F2 (5.5)
: : RNA.Base > 0.7343804: F3 (3.3/1.2)
: ALT.48 > 0.1685393:
: :...ALT.48 <= 0.2921348: F3 (10.2/1.7)
: ALT.48 > 0.2921348:
: :...Age > 0.03448276:
: :...RNA.Base > 0.3891023:
: : :...BMI <= 0.6153846: F1 (4.1/2.1)
: : : BMI > 0.6153846: F3 (11.1/1.1)
: : RNA.Base <= 0.3891023:
: : :...BMI <= 0.7692308: F3 (2.8/1.4)
: : BMI > 0.7692308:
: : :...ALT.1 <= 0.6404495: F1 (4.2)
: : ALT.1 > 0.6404495: F4 (2.1/0.3)
: Age <= 0.03448276:
: :...Plat > 0.6648883: F3 (5.3/2.3)
: Plat <= 0.6648883:
: :...RNA.4 <= 0.573199:
: :...ALT.48 <= 0.7303371: F4 (4.6)
: : ALT.48 > 0.7303371: F2 (2.7)
: RNA.4 > 0.573199:
: :...Age <= 0: F1 (3.3/0.2)
: Age > 0:
: :...WBC <= 0.5521405: F4 (3.3)
: WBC > 0.5521405: F1 (3.4)
Age > 0.137931:
:...WBC <= 0.0273326:
:...BMI <= 0.2307692: F3 (5.6/0.5)
: BMI > 0.2307692:
: :...AST.1 <= 0.07865169: F3 (2.5)
: AST.1 > 0.07865169: F2 (9.6/2.1)
WBC > 0.0273326:
:...AST.1 <= 0.6853933:
:...RNA.Base > 0.5308719:
: :...AST.1 > 0.5505618:
: : :...ALT.after.24.w <= 0.04347826:
: : : :...ALT.24 <= 0.4719101: F4 (7.2)
: : : : ALT.24 > 0.4719101: F2 (2.3)
: : : ALT.after.24.w > 0.04347826:
: : : :...ALT.1 > 0.6404495: F1 (11.1/1.9)
: : : ALT.1 <= 0.6404495:
: : : :...ALT.24 <= 0.2247191: F4 (8.1/1.8)
: : : ALT.24 > 0.2247191:
: : : :...RNA.Base <= 0.5988144: F2 (3/0.8)
: : : RNA.Base > 0.5988144:
: : : :...ALT.36 <= 0.1685393: F4 (3.5/1.7)
: : : ALT.36 > 0.1685393: F1 (18.9/5.1)
: : AST.1 <= 0.5505618:
: : :...Age > 0.862069:
: : :...ALT.36 <= 0.1460674: F1 (2.9)
: : : ALT.36 > 0.1460674:
: : : :...RNA.Base <= 0.5919006: F2 (2.9/0.9)
: : : RNA.Base > 0.5919006:
: : : :...WBC <= 0.2317234: F2 (2.2)
: : : WBC > 0.2317234:
: : : :...WBC > 0.8140505:
: : : :...AST.1 <= 0.2921348: F2 (4.3/0.8)
: : : : AST.1 > 0.2921348: F4 (5.2)
: : : WBC <= 0.8140505:
: : : :...ALT.12 <= 0.3820225: F4 (7.4)
: : : ALT.12 > 0.3820225:
: : : :...ALT.1 <= 0.7865168: F1 (4.5/0.7)
: : : ALT.1 > 0.7865168: F4 (3.1)
: : Age <= 0.862069:
: : :...ALT.12 > 0.8764045: F2 (3.3)
: : ALT.12 <= 0.8764045:
: : :...ALT.36 > 0.9213483:
: : :...Plat <= 0.5041176: F1 (5.7)
: : : Plat > 0.5041176: F2 (5.6/2.1)
: : ALT.36 <= 0.9213483:
: : :...ALT.12 <= 0.2696629:
: : :...BMI <= 0.1538462: F4 (6.7/1)
: : : BMI > 0.1538462:
: : : :...RBC <= 0.6825634:
: : : :...ALT.4 <= 0.3820225: F3 (5.6/0.9)
: : : : ALT.4 > 0.3820225: F4 (11.8/3.2)
: : : RBC > 0.6825634:
: : : :...Age <= 0.5517241: F3 (7.3)
: : : Age > 0.5517241: F1 (4.4/1.5)
: : ALT.12 > 0.2696629:
: : :...ALT.36 > 0.7640449:
: : :...BMI <= 0.3846154: F3 (7.4/0.4)
: : : BMI > 0.3846154:
: : : :...RNA.4 <= 0.8912042: F1 (6.2/1.4)
: : : RNA.4 > 0.8912042: F3 (2.4)
: : ALT.36 <= 0.7640449:
: : :...ALT.4 <= 0.2134831:
: : :...ALT.48 <= 0.5280899: F3 (9.1/0.6)
: : : ALT.48 > 0.5280899: F4 (4.8/2.1)
: : ALT.4 > 0.2134831:
: : :...ALT.4 > 0.9213483: F2 (6.9/1.5)
: : ALT.4 <= 0.9213483:
: : :...WBC <= 0.1154775: F2 (2.8/0.7)
: : WBC > 0.1154775: [S1]
: RNA.Base <= 0.5308719:
: :...RBC <= 0.03540597: F4 (7.8/1.8)
: RBC > 0.03540597:
: :...WBC <= 0.3774973:
: :...RNA.Base > 0.4313902:
: : :...ALT.1 <= 0.5280899: F4 (4.6)
: : : ALT.1 > 0.5280899: F2 (6.7/2.7)
: : RNA.Base <= 0.4313902:
: : :...ALT.36 <= 0.1685393: F3 (5.1/1.8)
: : ALT.36 > 0.1685393:
: : :...WBC > 0.1862788:
: : :...ALT.24 > 0.8202247:
: : : :...Plat <= 0.4920683: F3 (3.9)
: : : : Plat > 0.4920683: F1 (3.8/1.8)
: : : ALT.24 <= 0.8202247:
: : : :...ALT.after.24.w <= 0.6956522:
: : : :...Age <= 0.6551724: F1 (19.1/2.2)
: : : : Age > 0.6551724: F4 (5/1.4)
: : : ALT.after.24.w > 0.6956522:
: : : :...BMI <= 0.3846154: F1 (4.5/2.3)
: : : BMI > 0.3846154: F2 (2.5)
: : WBC <= 0.1862788:
: : :...WBC <= 0.06992316: F1 (7.2/2.5)
: : WBC > 0.06992316:
: : :...AST.1 <= 0.1123596: F1 (2.4/0.5)
: : AST.1 > 0.1123596:
: : :...RNA.4 <= 0.2932821: F4 (4/1.1)
: : RNA.4 > 0.2932821:
: : :...ALT.48 <= 0.8876405: F2 (14.5/3)
: : ALT.48 > 0.8876405: F3 (2.2)
: WBC > 0.3774973:
: :...ALT.4 <= 0.1011236:
: :...RBC <= 0.1031614: F2 (2.1)
: : RBC > 0.1031614:
: : :...ALT.36 <= 0.2808989: F1 (3.8/1.3)
: : ALT.36 > 0.2808989: F3 (7.8)
: ALT.4 > 0.1011236:
: :...AST.1 > 0.6179775:
: :...Plat <= 0.6845209: F3 (4/0.7)
: : Plat > 0.6845209: F1 (3.6)
: AST.1 <= 0.6179775:
: :...ALT.after.24.w <= 0.2173913:
: :...ALT.4 <= 0.2247191: F2 (6)
: : ALT.4 > 0.2247191:
: : :...RBC > 0.6763864: F2 (7.4/2.6)
: : RBC <= 0.6763864:
: : :...ALT.12 <= 0.05617978: F4 (3.3/1.6)
: : ALT.12 > 0.05617978: F3 (10.6/0.9)
: ALT.after.24.w > 0.2173913:
: :...ALT.1 <= 0.2247191:
: :...WBC > 0.9231614: F4 (2.9)
: : WBC <= 0.9231614:
: : :...RNA.Base > 0.3676065: F3 (8.8/1)
: : RNA.Base <= 0.3676065: [S2]
: ALT.1 > 0.2247191:
: :...RBC > 0.877557:
: :...Plat <= 0.7074507: F3 (4/0.3)
: : Plat > 0.7074507: F2 (2.1)
: RBC <= 0.877557:
: :...ALT.1 <= 0.3146068:
: :...RNA.4 <= 0.4080019: F4 (3.9)
: : RNA.4 > 0.4080019: F1 (3.7)
: ALT.1 > 0.3146068:
: :...WBC <= 0.413831: F1 (5.1/2.4)
: WBC > 0.413831: [S3]
AST.1 > 0.6853933:
:...ALT.1 <= 0.03370786: F1 (4.8/1)
ALT.1 > 0.03370786:
:...RBC <= 0.155027:
:...RNA.4 > 0.6988958: F3 (5.5/0.7)
: RNA.4 <= 0.6988958:
: :...ALT.after.24.w <= 0.8695652: F2 (12.3/2.6)
: ALT.after.24.w > 0.8695652: F3 (2.6)
RBC > 0.155027:
:...ALT.1 > 0.9775281: F2 (4.7)
ALT.1 <= 0.9775281:
:...BMI > 0.9230769: F3 (6.3/1.2)
BMI <= 0.9230769:
:...RNA.4 <= 0.09503957:
:...AST.1 > 0.9438202: F3 (2/0.2)
: AST.1 <= 0.9438202:
: :...WBC <= 0.3648738: F2 (3.1/1.1)
: WBC > 0.3648738: F4 (11.1)
RNA.4 > 0.09503957:
:...Age <= 0.2068966:
:...AST.1 <= 0.9438202: F4 (5.1)
: AST.1 > 0.9438202: F1 (2.7/0.8)
Age > 0.2068966:
:...RNA.Base > 0.7885553:
:...BMI <= 0.1538462: F3 (3.7)
: BMI > 0.1538462:
: :...RBC > 0.8693825: F4 (5.7/0.6)
: RBC <= 0.8693825:
: :...ALT.12 <= 0.752809: F2 (9/0.4)
: ALT.12 > 0.752809: F4 (2.9)
RNA.Base <= 0.7885553:
:...ALT.24 > 0.8876405:
:...RBC <= 0.7460993: F3 (7.1/1.3)
: RBC > 0.7460993: F1 (2.9)
ALT.24 <= 0.8876405:
:...WBC <= 0.1070252: F4 (6.9/1.8)
WBC > 0.1070252:
:...ALT.4 > 0.5955056: [S4]
ALT.4 <= 0.5955056: [S5]
SubTree [S1]
ALT.1 > 0.7865168: F4 (7.4/1.7)
ALT.1 <= 0.7865168:
:...ALT.36 > 0.6179775: F1 (5.2/1.1)
ALT.36 <= 0.6179775:
:...ALT.1 <= 0.7303371: F4 (18.3/7.2)
ALT.1 > 0.7303371: F1 (3.7)
SubTree [S2]
ALT.after.24.w > 0.6521739: F1 (2.3/0.7)
ALT.after.24.w <= 0.6521739:
:...ALT.48 <= 0.5168539: F2 (3.9)
ALT.48 > 0.5168539: F3 (3.5/0.5)
SubTree [S3]
ALT.after.24.w <= 0.5652174:
:...ALT.12 > 0.7640449:
: :...Age <= 0.4827586: F3 (2)
: : Age > 0.4827586: F2 (5)
: ALT.12 <= 0.7640449:
: :...Age > 0.862069: F3 (2.4/1)
: Age <= 0.862069:
: :...Age <= 0.2068966: F2 (2.6)
: Age > 0.2068966: F4 (13.1/1.6)
ALT.after.24.w > 0.5652174:
:...ALT.12 > 0.7078652: F1 (4.2)
ALT.12 <= 0.7078652:
:...Plat <= 0.05881559: F1 (2.2)
Plat > 0.05881559:
:...ALT.24 <= 0.4831461: F4 (5.6/1)
ALT.24 > 0.4831461: F2 (10.6/1.5)
SubTree [S4]
ALT.48 <= 0.1797753: F2 (4.8/1.1)
ALT.48 > 0.1797753:
:...WBC <= 0.3881449: F1 (8.2/1.6)
WBC > 0.3881449:
:...ALT.48 <= 0.6629214: F3 (8.2/0.2)
ALT.48 > 0.6629214:
:...Age <= 0.5862069: F1 (2.8)
Age > 0.5862069: F3 (4.2/1.1)
SubTree [S5]
RNA.4 <= 0.1763387: F1 (4/1.3)
RNA.4 > 0.1763387:
:...RBC <= 0.2396906: F2 (3.6/1.6)
RBC > 0.2396906:
:...ALT.24 > 0.741573:
:...Plat <= 0.5066878: F4 (5.6)
: Plat > 0.5066878: F2 (6.4)
ALT.24 <= 0.741573:
:...ALT.1 <= 0.4831461:
:...ALT.1 <= 0.3033708: F3 (7/1.5)
: ALT.1 > 0.3033708: F4 (6.4/0.3)
ALT.1 > 0.4831461:
:...ALT.1 > 0.7752809: F3 (5.9/1)
ALT.1 <= 0.7752809:
:...RBC <= 0.4494309: F3 (2.3)
RBC > 0.4494309:
:...WBC <= 0.8934138: F2 (8.4)
WBC > 0.8934138: F3 (2)
----- Trial 12: -----
Decision tree:
ALT.after.24.w > 0.8260869:
:...ALT.36 > 0.8764045:
: :...ALT.4 <= 0.3595506: F4 (8.5/1)
: : ALT.4 > 0.3595506:
: : :...RNA.4 > 0.7324504: F1 (3)
: : RNA.4 <= 0.7324504:
: : :...ALT.24 <= 0.8764045: F2 (6.5/1.2)
: : ALT.24 > 0.8764045: F4 (2.4)
: ALT.36 <= 0.8764045:
: :...ALT.24 <= 0.04494382: F1 (7.4/1.3)
: ALT.24 > 0.04494382:
: :...ALT.48 > 0.8764045:
: :...Age <= 0.2758621: F4 (3.9/2.4)
: : Age > 0.2758621: F2 (11.5/4.1)
: ALT.48 <= 0.8764045:
: :...ALT.48 > 0.7865168:
: :...ALT.4 <= 0.1460674: F4 (2.2)
: : ALT.4 > 0.1460674: F1 (10/1.6)
: ALT.48 <= 0.7865168:
: :...RNA.4 <= 0.5460011:
: :...ALT.1 > 0.4831461:
: : :...RNA.4 <= 0.01073637: F1 (2.7)
: : : RNA.4 > 0.01073637:
: : : :...Age > 0.6896552:
: : : :...RNA.4 <= 0.1096454: F2 (2.4)
: : : : RNA.4 > 0.1096454: F3 (6.5/1.7)
: : : Age <= 0.6896552:
: : : :...ALT.4 > 0.7303371: F1 (4.3/1.9)
: : : ALT.4 <= 0.7303371:
: : : :...WBC <= 0.559495: F3 (10.6)
: : : WBC > 0.559495: F1 (3.8/1)
: : ALT.1 <= 0.4831461:
: : :...RNA.4 > 0.3680356: F1 (5.4/2.4)
: : RNA.4 <= 0.3680356:
: : :...WBC <= 0.3929748: F3 (6.1/0.3)
: : WBC > 0.3929748:
: : :...ALT.36 <= 0.1011236: F3 (3.1/1.4)
: : ALT.36 > 0.1011236:
: : :...ALT.12 > 0.3707865: F4 (9.3)
: : ALT.12 <= 0.3707865:
: : :...ALT.after.24.w <= 0.8695652: F4 (3.1)
: : ALT.after.24.w > 0.8695652: F3 (3.8/0.8)
: RNA.4 > 0.5460011:
: :...WBC <= 0.033809: F3 (3.9)
: WBC > 0.033809:
: :...WBC <= 0.4010977:
: :...RNA.4 > 0.8762014: F2 (3.8/0.6)
: : RNA.4 <= 0.8762014:
: : :...AST.1 <= 0.4157303:
: : :...AST.1 <= 0.2134831: F1 (4.1)
: : : AST.1 > 0.2134831: F2 (4.6/2.2)
: : AST.1 > 0.4157303:
: : :...AST.1 <= 0.7303371: F4 (9.9)
: : AST.1 > 0.7303371: F1 (3.1/0.9)
: WBC > 0.4010977:
: :...RBC > 0.8104688:
: :...ALT.24 <= 0.3595506: F4 (2.8)
: : ALT.24 > 0.3595506: F3 (5.7/0.6)
: RBC <= 0.8104688:
: :...ALT.after.24.w > 0.9565217: F4 (4.4/1.4)
: ALT.after.24.w <= 0.9565217:
: :...ALT.24 > 0.494382: F1 (9.7/1)
: ALT.24 <= 0.494382:
: :...RNA.4 <= 0.7702832: F1 (3.7/0.4)
: RNA.4 > 0.7702832: F4 (5.1/0.4)
ALT.after.24.w <= 0.8260869:
:...ALT.4 > 0.9213483:
:...ALT.after.24.w > 0.7391304: F3 (5.1/1.5)
: ALT.after.24.w <= 0.7391304:
: :...Age <= 0.3793103:
: :...AST.1 <= 0.3483146: F3 (4.3/1.3)
: : AST.1 > 0.3483146:
: : :...AST.1 <= 0.8988764: F1 (8.3/2.1)
: : AST.1 > 0.8988764: F2 (3.4)
: Age > 0.3793103:
: :...ALT.12 <= 0.4606742:
: :...ALT.24 <= 0.4606742: F1 (3.8)
: : ALT.24 > 0.4606742:
: : :...ALT.24 <= 0.8988764: F4 (3.4/0.4)
: : ALT.24 > 0.8988764: F1 (2.4)
: ALT.12 > 0.4606742:
: :...Plat <= 0.2486081:
: :...BMI <= 0.3076923: F4 (4.1)
: : BMI > 0.3076923: F1 (2.4/0.5)
: Plat > 0.2486081:
: :...AST.1 <= 0.5505618: F2 (9.8)
: AST.1 > 0.5505618:
: :...Age <= 0.7931035: F4 (2.5)
: Age > 0.7931035: F2 (4.2/2.1)
ALT.4 <= 0.9213483:
:...ALT.4 <= 0.06741573:
:...ALT.4 > 0.05617978: F1 (7.2/1.6)
: ALT.4 <= 0.05617978:
: :...ALT.after.24.w <= 0.3478261:
: :...ALT.24 > 0.8764045: F2 (4.7/0.7)
: : ALT.24 <= 0.8764045:
: : :...ALT.after.24.w <= 0.08695652: F1 (6.8/0.9)
: : ALT.after.24.w > 0.08695652:
: : :...ALT.24 <= 0.5393258:
: : :...Age <= 0.3793103: F2 (3.8)
: : : Age > 0.3793103: F4 (4.9)
: : ALT.24 > 0.5393258:
: : :...ALT.48 <= 0.8314607: F1 (6.5/0.8)
: : ALT.48 > 0.8314607: F4 (2.2)
: ALT.after.24.w > 0.3478261:
: :...RNA.Base > 0.8781575: F4 (3.6/0.8)
: RNA.Base <= 0.8781575:
: :...ALT.12 <= 0.4606742:
: :...ALT.12 <= 0.1573034: F1 (4.3/1.7)
: : ALT.12 > 0.1573034: F2 (10.3/2.9)
: ALT.12 > 0.4606742:
: :...RNA.4 > 0.6053365: F3 (6.6)
: RNA.4 <= 0.6053365:
: :...AST.1 <= 0.7303371: F1 (4.5)
: AST.1 > 0.7303371: F3 (4/1.4)
ALT.4 > 0.06741573:
:...ALT.4 <= 0.4831461:
:...ALT.36 <= 0.08988764:
: :...RNA.4 <= 0.2005842: F3 (4.8)
: : RNA.4 > 0.2005842:
: : :...ALT.48 <= 0.3033708:
: : :...WBC <= 0.807135: F2 (7.6/2.5)
: : : WBC > 0.807135: F3 (5.8/0.7)
: : ALT.48 > 0.3033708:
: : :...WBC <= 0.3476399: F2 (3.8/1.8)
: : WBC > 0.3476399:
: : :...ALT.36 <= 0.05617978: F4 (8.5)
: : ALT.36 > 0.05617978:
: : :...AST.1 <= 0.2022472: F4 (4.5/0.6)
: : AST.1 > 0.2022472: F2 (3.7)
: ALT.36 > 0.08988764:
: :...ALT.after.24.w > 0.6086956:
: :...ALT.24 > 0.8876405: F1 (2.7)
: : ALT.24 <= 0.8876405:
: : :...Plat <= 0.3807915:
: : :...ALT.48 > 0.9101124: F3 (4.3)
: : : ALT.48 <= 0.9101124:
: : : :...ALT.4 <= 0.3483146: F4 (14.9/3)
: : : ALT.4 > 0.3483146:
: : : :...ALT.1 <= 0.247191: F3 (2.9/1.3)
: : : ALT.1 > 0.247191: F2 (4.2)
: : Plat > 0.3807915:
: : :...ALT.after.24.w <= 0.6521739: F2 (4.4/0.9)
: : ALT.after.24.w > 0.6521739:
: : :...ALT.36 <= 0.2359551: F1 (4.9/1.6)
: : ALT.36 > 0.2359551:
: : :...ALT.12 <= 0.2022472: F1 (5.1/2.8)
: : ALT.12 > 0.2022472:
: : :...ALT.1 > 0.8651685: F4 (4.3)
: : ALT.1 <= 0.8651685:
: : :...BMI <= 0.3846154:
: : :...ALT.24 <= 0.7640449: F2 (4.7/2.1)
: : : ALT.24 > 0.7640449: F4 (2.6)
: : BMI > 0.3846154:
: : :...ALT.36 <= 0.8089887: F2 (12.8/0.3)
: : ALT.36 > 0.8089887: F4 (5.4/1.4)
: ALT.after.24.w <= 0.6086956:
: :...RBC <= 0.06745344:
: :...ALT.1 <= 0.5955056: F3 (8/1.2)
: : ALT.1 > 0.5955056: F2 (4.2)
: RBC > 0.06745344:
: :...ALT.after.24.w <= 0.08695652:
: :...Plat > 0.5515208:
: : :...ALT.12 <= 0.6741573:
: : : :...ALT.36 <= 0.5842696: F4 (4.9/1.8)
: : : : ALT.36 > 0.5842696: F3 (5)
: : : ALT.12 > 0.6741573:
: : : :...ALT.1 <= 0.5955056: F4 (8.7/1.2)
: : : ALT.1 > 0.5955056: F2 (2.4)
: : Plat <= 0.5515208:
: : :...Plat <= 0.1263235:
: : :...BMI <= 0.6923077: F1 (3.3/1.2)
: : : BMI > 0.6923077: F4 (4.2/1.3)
: : Plat > 0.1263235:
: : :...ALT.24 > 0.5730337:
: : :...RBC <= 0.5236695: F4 (2.2/0.8)
: : : RBC > 0.5236695: F2 (4.1/0.3)
: : ALT.24 <= 0.5730337:
: : :...BMI <= 0.3076923: F2 (6.8)
: : BMI > 0.3076923:
: : :...WBC <= 0.1981339: F2 (3.4)
: : WBC > 0.1981339: F1 (3.5)
: ALT.after.24.w > 0.08695652:
: :...RNA.Base > 0.7546256:
: :...ALT.36 <= 0.1910112: F1 (3.5/0.4)
: : ALT.36 > 0.1910112:
: : :...BMI <= 0.3846154:
: : :...BMI > 0.2307692: F3 (7.6)
: : : BMI <= 0.2307692:
: : : :...RNA.4 <= 0.4043105: F3 (6.2)
: : : RNA.4 > 0.4043105: F1 (4.8/0.9)
: : BMI > 0.3846154:
: : :...ALT.after.24.w <= 0.2608696: F4 (3.4/0.9)
: : ALT.after.24.w > 0.2608696:
: : :...BMI <= 0.6923077: F2 (5.8/1.8)
: : BMI > 0.6923077: F3 (5.7/1.1)
: RNA.Base <= 0.7546256:
: :...ALT.12 <= 0.4606742:
: :...WBC <= 0.1706915: F3 (6.9)
: : WBC > 0.1706915:
: : :...Plat > 0.8699598:
: : :...AST.1 <= 0.3033708: F1 (2.5/0.8)
: : : AST.1 > 0.3033708: F2 (5)
: : Plat <= 0.8699598:
: : :...ALT.24 > 0.4719101:
: : :...RNA.4 <= 0.4080019: F1 (9.2/1.8)
: : : RNA.4 > 0.4080019: F3 (3.8/0.5)
: : ALT.24 <= 0.4719101:
: : :...Age > 0.9310345: F2 (2.3/1)
: : Age <= 0.9310345:
: : :...ALT.48 > 0.8089887: F3 (3.7/1.4)
: : ALT.48 <= 0.8089887: [S1]
: ALT.12 > 0.4606742:
: :...ALT.48 <= 0.08988764: F4 (12.4)
: ALT.48 > 0.08988764:
: :...ALT.36 <= 0.1348315: F2 (5.9/1.2)
: ALT.36 > 0.1348315:
: :...ALT.24 <= 0.02247191: F2 (4.4/1.8)
: ALT.24 > 0.02247191:
: :...Age <= 0: F2 (2.5)
: Age > 0:
: :...ALT.after.24.w > 0.3478261:
: :...Plat <= 0.7074507: F4 (20.6/4.7)
: : Plat > 0.7074507: F3 (3.3/0.5)
: ALT.after.24.w <= 0.3478261: [S2]
ALT.4 > 0.4831461:
:...ALT.48 > 0.9662921:
:...ALT.48 <= 0.9775281: F4 (2.6)
: ALT.48 > 0.9775281:
: :...RNA.4 <= 0.1295362: F4 (2.2)
: RNA.4 > 0.1295362: F3 (7.7/0.8)
ALT.48 <= 0.9662921:
:...WBC <= 0.2394072:
:...ALT.after.24.w <= 0.1304348:
: :...ALT.12 <= 0.6067415: F4 (12.8/4.9)
: : ALT.12 > 0.6067415: F2 (8/1)
: ALT.after.24.w > 0.1304348:
: :...ALT.after.24.w > 0.7391304:
: :...ALT.24 <= 0.3595506: F4 (2.5)
: : ALT.24 > 0.3595506: F2 (3.9/0.8)
: ALT.after.24.w <= 0.7391304:
: :...Age <= 0.137931: F1 (7/2.2)
: Age > 0.137931:
: :...Age > 0.9310345: F1 (2.1/1)
: Age <= 0.9310345:
: :...ALT.36 <= 0.2022472: F2 (5.5/2)
: ALT.36 > 0.2022472:
: :...RNA.Base <= 0.1265625: F4 (2.1)
: RNA.Base > 0.1265625:
: :...RNA.Base > 0.8316774: F4 (5.9/2.1)
: RNA.Base <= 0.8316774:
: :...RNA.Base <= 0.2426743: F2 (2.5/0.4)
: RNA.Base > 0.2426743: F1 (18.1/2.4)
WBC > 0.2394072:
:...ALT.48 > 0.9438202: F2 (8.1/2)
ALT.48 <= 0.9438202:
:...AST.1 > 0.9662921:
:...WBC <= 0.7245884: F2 (5.7/0.8)
: WBC > 0.7245884: F3 (3.3/1)
AST.1 <= 0.9662921:
:...WBC <= 0.4657519:
:...RBC <= 0.1731223:
: :...RNA.4 <= 0.5543501: F4 (4.8/0.6)
: : RNA.4 > 0.5543501: F1 (7.9)
: RBC > 0.1731223:
: :...WBC > 0.3695939:
: :...ALT.12 <= 0.247191:
: : :...Age <= 0.4827586: F3 (3.6)
: : : Age > 0.4827586: F2 (3.4/0.6)
: : ALT.12 > 0.247191:
: : :...ALT.24 <= 0.7078652: F3 (15.6/2.5)
: : ALT.24 > 0.7078652: F4 (2.7)
: WBC <= 0.3695939:
: :...ALT.4 > 0.8651685: F1 (6.9/2.3)
: ALT.4 <= 0.8651685:
: :...RNA.Base <= 0.3449243: F1 (8.6/1.8)
: RNA.Base > 0.3449243:
: :...ALT.24 > 0.9438202: F1 (2/0.8)
: ALT.24 <= 0.9438202:
: :...ALT.1 > 0.741573: [S3]
: ALT.1 <= 0.741573: [S4]
WBC > 0.4657519:
:...WBC <= 0.5047201: F4 (10.5/2.7)
WBC > 0.5047201:
:...ALT.4 <= 0.5168539:
:...RNA.Base <= 0.1532319: F1 (2.3)
: RNA.Base > 0.1532319:
: :...ALT.after.24.w <= 0.2173913: F4 (4.2)
: ALT.after.24.w > 0.2173913: F2 (6.2/0.9)
ALT.4 > 0.5168539:
:...BMI <= 0.2307692:
:...RBC <= 0.1887841:
: :...Plat <= 0.367146: F2 (2.4/1)
: : Plat > 0.367146: F3 (5.3/0.7)
: RBC > 0.1887841:
: :...BMI <= 0: F1 (2.2)
: BMI > 0:
: :...RNA.4 <= 0.1450841: F4 (5.1)
: RNA.4 > 0.1450841:
: :...RBC > 0.803508: F3 (5.6/3.4)
: RBC <= 0.803508:
: :...ALT.1 <= 0.6853933: [S5]
: ALT.1 > 0.6853933: [S6]
BMI > 0.2307692:
:...ALT.24 <= 0.3595506:
:...RNA.4 > 0.7443044: F1 (6.5/1.3)
: RNA.4 <= 0.7443044:
: :...ALT.48 <= 0.1910112: F4 (3.6/1)
: ALT.48 > 0.1910112: [S7]
ALT.24 > 0.3595506:
:...AST.1 <= 0.1235955:
:...RBC <= 0.6728839: F3 (8.8/2.1)
: RBC > 0.6728839: F4 (3.5)
AST.1 > 0.1235955:
:...Plat > 0.7143146: F2 (10.2/0.6)
Plat <= 0.7143146:
:...BMI <= 0.3076923: [S8]
BMI > 0.3076923: [S9]
SubTree [S1]
AST.1 <= 0.2247191: F1 (4.4/0.5)
AST.1 > 0.2247191: F4 (11.3/2.8)
SubTree [S2]
ALT.12 <= 0.5280899: F4 (3.2/0.3)
ALT.12 > 0.5280899:
:...ALT.after.24.w > 0.2173913: F3 (12.7/1.2)
ALT.after.24.w <= 0.2173913:
:...ALT.after.24.w <= 0.1304348: F3 (3.9/1.8)
ALT.after.24.w > 0.1304348: F4 (5.3/2.2)
SubTree [S3]
ALT.36 <= 0.4719101: F3 (3.7)
ALT.36 > 0.4719101: F1 (2.4/0.4)
SubTree [S4]
RNA.4 > 0.4249694: F3 (8.4)
RNA.4 <= 0.4249694:
:...ALT.after.24.w <= 0.1304348: F3 (3)
ALT.after.24.w > 0.1304348: F2 (3)
SubTree [S5]
WBC <= 0.683315: F4 (3.8/0.2)
WBC > 0.683315: F3 (4.6/1.1)
SubTree [S6]
AST.1 <= 0.2134831: F4 (3.4/1)
AST.1 > 0.2134831: F1 (4.8)
SubTree [S7]
RNA.4 <= 0.2047033: F1 (4/1.6)
RNA.4 > 0.2047033: F3 (14.1/1.5)
SubTree [S8]
ALT.after.24.w <= 0.3043478: F1 (2.7/1.3)
ALT.after.24.w > 0.3043478: F3 (4)
SubTree [S9]
Plat > 0.6313029: F1 (4.6/0.8)
Plat <= 0.6313029:
:...RNA.Base > 0.8509701: F2 (5.5/0.4)
RNA.Base <= 0.8509701:
:...BMI <= 0.3846154: F2 (3.5)
BMI > 0.3846154:
:...ALT.after.24.w > 0.7391304: F3 (2.2/0.4)
ALT.after.24.w <= 0.7391304:
:...RNA.Base > 0.7192066: F1 (4.2)
RNA.Base <= 0.7192066:
:...RNA.4 > 0.5460011:
:...ALT.48 <= 0.5842696: F3 (2.4/0.9)
: ALT.48 > 0.5842696: F1 (4.3)
RNA.4 <= 0.5460011:
:...BMI > 0.7692308: F2 (5.8/1.6)
BMI <= 0.7692308:
:...ALT.1 <= 0.6966292: F3 (4.7)
ALT.1 > 0.6966292: F2 (3.9/0.5)
----- Trial 13: -----
Decision tree:
BMI <= 0.4615385:
:...AST.1 > 0.7078652:
: :...RNA.4 > 0.9459562: F1 (5.4/1.2)
: : RNA.4 <= 0.9459562:
: : :...ALT.24 > 0.9662921: F1 (5.3/1.8)
: : ALT.24 <= 0.9662921:
: : :...ALT.48 <= 0.08988764:
: : :...RBC <= 0.2843642: F3 (3.1)
: : : RBC > 0.2843642:
: : : :...ALT.4 <= 0.8202247: F4 (9.3/1.7)
: : : ALT.4 > 0.8202247: F2 (2.2)
: : ALT.48 > 0.08988764:
: : :...RNA.4 <= 0.1096454:
: : :...Age <= 0.06896552: F3 (2.2/0.9)
: : : Age > 0.06896552:
: : : :...Plat <= 0.452106: F4 (4.8/0.3)
: : : Plat > 0.452106: F2 (6.4/1.9)
: : RNA.4 > 0.1096454:
: : :...ALT.36 > 0.8539326:
: : :...AST.1 <= 0.8202247: F3 (8.9/2)
: : : AST.1 > 0.8202247:
: : : :...AST.1 <= 0.8988764: F4 (3.9)
: : : AST.1 > 0.8988764: F3 (2.5)
: : ALT.36 <= 0.8539326:
: : :...RBC <= 0.4163593:
: : :...Age <= 0.2758621: F3 (10.1/1.4)
: : : Age > 0.2758621:
: : : :...RBC > 0.3142412: F3 (3.7/0.4)
: : : RBC <= 0.3142412:
: : : :...ALT.36 > 0.4606742: F2 (9.5/1)
: : : ALT.36 <= 0.4606742:
: : : :...RBC <= 0.1343212: F2 (3.1/0.2)
: : : RBC > 0.1343212: F3 (3/0.5)
: : RBC > 0.4163593:
: : :...ALT.12 <= 0.1011236: F1 (3.4)
: : ALT.12 > 0.1011236:
: : :...ALT.after.24.w > 0.9130435: F3 (3)
: : ALT.after.24.w <= 0.9130435:
: : :...RNA.4 > 0.8504306: F3 (3.3)
: : RNA.4 <= 0.8504306:
: : :...BMI <= 0.1538462:
: : :...ALT.4 <= 0.6292135: F2 (11.5/3.3)
: : : ALT.4 > 0.6292135: F3 (4.4/1.1)
: : BMI > 0.1538462:
: : :...BMI <= 0.2307692: F1 (3)
: : BMI > 0.2307692: [S1]
: AST.1 <= 0.7078652:
: :...ALT.after.24.w <= 0.4782609:
: :...Plat > 0.8100426:
: : :...ALT.12 > 0.7640449: F4 (6/2.9)
: : : ALT.12 <= 0.7640449:
: : : :...ALT.36 <= 0.3033708:
: : : :...RNA.Base <= 0.2462527: F3 (3.7)
: : : : RNA.Base > 0.2462527: F1 (5/0.3)
: : : ALT.36 > 0.3033708:
: : : :...ALT.24 > 0.7191011: F1 (7.3)
: : : ALT.24 <= 0.7191011:
: : : :...ALT.24 <= 0.4494382: F1 (6.8/2.2)
: : : ALT.24 > 0.4494382: F4 (3.2/0.4)
: : Plat <= 0.8100426:
: : :...Age <= 0.06896552:
: : :...WBC <= 0.1835346: F4 (2.5/1.1)
: : : WBC > 0.1835346:
: : : :...ALT.1 <= 0.1910112: F1 (2.4)
: : : ALT.1 > 0.1910112:
: : : :...RNA.Base <= 0.3681011: F4 (4)
: : : RNA.Base > 0.3681011:
: : : :...ALT.1 <= 0.6853933: F1 (3.8)
: : : ALT.1 > 0.6853933: F4 (3.3/0.3)
: : Age > 0.06896552:
: : :...WBC > 0.9231614: F4 (10.7/1.5)
: : WBC <= 0.9231614:
: : :...Plat > 0.6938502:
: : :...ALT.12 <= 0.08988764: F3 (3.3)
: : : ALT.12 > 0.08988764:
: : : :...RBC <= 0.559118: F2 (7.4/2)
: : : RBC > 0.559118: F4 (11.6/1)
: : Plat <= 0.6938502:
: : :...ALT.1 <= 0.08988764: F3 (6.1/1)
: : ALT.1 > 0.08988764:
: : :...ALT.12 > 0.8876405: F1 (9.1/3.1)
: : ALT.12 <= 0.8876405:
: : :...Plat <= 0.06298941: F2 (6.8/1.3)
: : Plat > 0.06298941:
: : :...ALT.after.24.w <= 0.08695652:
: : :...ALT.36 > 0.9213483: F3 (2.4/1)
: : : ALT.36 <= 0.9213483:
: : : :...ALT.1 <= 0.6853933:
: : : :...ALT.12 <= 0.4719101: F2 (11.1/1.1)
: : : : ALT.12 > 0.4719101: F4 (3/0.5)
: : : ALT.1 > 0.6853933:
: : : :...RBC <= 0.4720992: F1 (2.5)
: : : RBC > 0.4720992: F2 (3.7/0.8)
: : ALT.after.24.w > 0.08695652:
: : :...ALT.36 > 0.6629214:
: : :...ALT.36 > 0.9101124: F1 (3.9/1.4)
: : : ALT.36 <= 0.9101124:
: : : :...WBC > 0.5600439: F4 (5.8)
: : : WBC <= 0.5600439:
: : : :...ALT.36 <= 0.8764045: F1 (6.9/1.5)
: : : ALT.36 > 0.8764045: F4 (2.8)
: : ALT.36 <= 0.6629214:
: : :...ALT.1 > 0.7640449:
: : :...RNA.Base <= 0.2498062: F2 (3.5)
: : : RNA.Base > 0.2498062: F1 (5.8/1.6)
: : ALT.1 <= 0.7640449:
: : :...BMI > 0.3076923:
: : :...WBC <= 0.4782656: F4 (3.4/0.6)
: : : WBC > 0.4782656: F2 (3.8)
: : BMI <= 0.3076923:
: : :...ALT.1 <= 0.3595506: [S2]
: : ALT.1 > 0.3595506: [S3]
: ALT.after.24.w > 0.4782609:
: :...Age <= 0.03448276:
: :...RBC > 0.7366652: F3 (5.2/1.5)
: : RBC <= 0.7366652:
: : :...ALT.36 <= 0.258427: F2 (3.6/0.9)
: : ALT.36 > 0.258427: F4 (4)
: Age > 0.03448276:
: :...Age <= 0.2068966:
: :...AST.1 <= 0.04494382: F3 (3.6)
: : AST.1 > 0.04494382:
: : :...BMI <= 0.07692308:
: : :...ALT.after.24.w <= 0.6086956: F3 (6.1/1.2)
: : : ALT.after.24.w > 0.6086956: F1 (3.1)
: : BMI > 0.07692308:
: : :...RBC <= 0.4679978: F1 (7.8)
: : RBC > 0.4679978:
: : :...ALT.4 <= 0.1797753: F1 (2.1)
: : ALT.4 > 0.1797753: F4 (5.6/1)
: Age > 0.2068966:
: :...RBC <= 0.05493545:
: :...ALT.4 <= 0.8089887: F4 (6.9)
: : ALT.4 > 0.8089887: F3 (3.5/0.6)
: RBC > 0.05493545:
: :...Age <= 0.3103448:
: :...Plat > 0.6489123: F3 (5/2.3)
: : Plat <= 0.6489123:
: : :...ALT.1 <= 0.2247191: F3 (2.8)
: : ALT.1 > 0.2247191: F4 (9.2/0.9)
: Age > 0.3103448:
: :...ALT.24 > 0.8764045:
: :...BMI <= 0.07692308: F4 (2.2)
: : BMI > 0.07692308:
: : :...Plat <= 0.3123768: F1 (5)
: : Plat > 0.3123768: F4 (3.7/1.2)
: ALT.24 <= 0.8764045:
: :...AST.1 <= 0.1123596:
: :...RBC > 0.9188272: F3 (2.3)
: : RBC <= 0.9188272:
: : :...RNA.4 <= 0.2307412: F4 (4.5)
: : RNA.4 > 0.2307412:
: : :...RNA.4 <= 0.8535137: F1 (9.3/0.7)
: : RNA.4 > 0.8535137: F4 (2.7)
: AST.1 > 0.1123596:
: :...ALT.12 > 0.8202247:
: :...RBC <= 0.169807: F1 (5.2/2.3)
: : RBC > 0.169807:
: : :...WBC <= 0.2817783: F3 (2.6)
: : WBC > 0.2817783: F4 (10.3/1.2)
: ALT.12 <= 0.8202247:
: :...ALT.1 > 0.8314607:
: :...ALT.12 <= 0.4157303: F3 (8/0.4)
: : ALT.12 > 0.4157303: F4 (3.9/1)
: ALT.1 <= 0.8314607:
: :...Age <= 0.3793103: F3 (7.1/1.8)
: Age > 0.3793103:
: :...BMI > 0.3846154:
: :...ALT.4 <= 0.5842696: F3 (2.3)
: : ALT.4 > 0.5842696: F1 (5.5/1.7)
: BMI <= 0.3846154:
: :...RNA.4 <= 0.2941101:
: :...WBC > 0.5210757: F2 (5.2/0.3)
: : WBC <= 0.5210757: [S4]
: RNA.4 > 0.2941101:
: :...ALT.12 <= 0.08988764: F3 (4.9/1.5)
: ALT.12 > 0.08988764: [S5]
BMI > 0.4615385:
:...ALT.1 <= 0.01123596: F2 (13.2/3.5)
ALT.1 > 0.01123596:
:...WBC <= 0.04643249:
:...WBC <= 0.01317234: F2 (4.2/1.1)
: WBC > 0.01317234:
: :...RBC > 0.6685579: F1 (5.4)
: RBC <= 0.6685579:
: :...WBC <= 0.03556531: F3 (7/0.7)
: WBC > 0.03556531: F1 (2.4)
WBC > 0.04643249:
:...Age <= 0.5517241:
:...ALT.36 <= 0.05617978:
: :...Plat > 0.7939543: F4 (6.1/0.8)
: : Plat <= 0.7939543:
: : :...ALT.48 <= 0.5842696: F3 (9.5/1.1)
: : ALT.48 > 0.5842696: F4 (3.3)
: ALT.36 > 0.05617978:
: :...BMI <= 0.6153846:
: :...Plat <= 0.03117998: F1 (3)
: : Plat > 0.03117998:
: : :...ALT.1 > 0.7303371:
: : :...AST.1 > 0.8988764: F2 (3.8)
: : : AST.1 <= 0.8988764:
: : : :...Plat <= 0.4799589: F4 (8.1/0.7)
: : : Plat > 0.4799589: F1 (8.3/2.6)
: : ALT.1 <= 0.7303371:
: : :...WBC <= 0.3648738:
: : :...ALT.4 <= 0.7640449: F3 (7.8/1)
: : : ALT.4 > 0.7640449: F2 (3.1/1.1)
: : WBC > 0.3648738:
: : :...ALT.after.24.w > 0.8695652: F4 (3.8)
: : ALT.after.24.w <= 0.8695652:
: : :...RNA.Base <= 0.1641979: F3 (2.2/0.2)
: : RNA.Base > 0.1641979:
: : :...ALT.36 <= 0.2247191: F2 (7.9/0.4)
: : ALT.36 > 0.2247191:
: : :...ALT.48 <= 0.3033708: F2 (6.6/1.1)
: : ALT.48 > 0.3033708:
: : :...ALT.12 <= 0.494382: F3 (4.5/0.5)
: : ALT.12 > 0.494382: F4 (5.6)
: BMI > 0.6153846:
: :...Age <= 0.2413793:
: :...AST.1 <= 0.247191:
: : :...WBC <= 0.5959385: F3 (18.6/4.8)
: : : WBC > 0.5959385:
: : : :...ALT.36 <= 0.8202247: F3 (5.8/0.9)
: : : ALT.36 > 0.8202247: F2 (3.8)
: : AST.1 > 0.247191:
: : :...Plat <= 0.06908154: F2 (5.5/0.8)
: : Plat > 0.06908154:
: : :...Plat > 0.6405048:
: : :...ALT.12 > 0.5617977:
: : : :...ALT.24 <= 0.6067415: F1 (2.2)
: : : : ALT.24 > 0.6067415: F3 (7.5/1.2)
: : : ALT.12 <= 0.5617977:
: : : :...Plat > 0.8756548: F3 (6.4/1.9)
: : : Plat <= 0.8756548:
: : : :...ALT.36 <= 0.3595506: F2 (4.4)
: : : ALT.36 > 0.3595506: F4 (3.7)
: : Plat <= 0.6405048:
: : :...RNA.Base <= 0.4264929:
: : :...RBC <= 0.9284534: F1 (19.6/2.8)
: : : RBC > 0.9284534: F2 (2)
: : RNA.Base > 0.4264929:
: : :...BMI > 0.9230769: F4 (2.2/0.3)
: : BMI <= 0.9230769:
: : :...RBC <= 0.3553458: F1 (5.7/1.1)
: : RBC > 0.3553458:
: : :...RBC <= 0.9111203: F3 (7.5/0.8)
: : RBC > 0.9111203: F1 (3.2/0.3)
: Age > 0.2413793:
: :...ALT.36 <= 0.1460674: F2 (5.5/1.7)
: ALT.36 > 0.1460674:
: :...Plat > 0.9416265: F2 (5/1)
: Plat <= 0.9416265:
: :...RNA.Base <= 0.282621:
: :...ALT.48 <= 0.3707865: F4 (6.4/1.6)
: : ALT.48 > 0.3707865:
: : :...RNA.4 <= 0.1763387: F3 (2.7/1.5)
: : RNA.4 > 0.1763387:
: : :...BMI > 0.9230769: F3 (3.6)
: : BMI <= 0.9230769:
: : :...WBC <= 0.4350165: F1 (4.7)
: : WBC > 0.4350165: F3 (8.4/2.6)
: RNA.Base > 0.282621:
: :...RBC <= 0.2128093: F3 (7.7/2.9)
: RBC > 0.2128093:
: :...ALT.4 <= 0.5393258: F4 (18.6/4.1)
: ALT.4 > 0.5393258:
: :...Age > 0.4137931: F3 (3.9)
: Age <= 0.4137931:
: :...RBC <= 0.4832055: F3 (3.8/0.8)
: RBC > 0.4832055: F4 (6.3/0.3)
Age > 0.5517241:
:...WBC <= 0.1086718:
:...AST.1 <= 0.8089887: F2 (7.7/0.1)
: AST.1 > 0.8089887: F3 (4.6)
WBC > 0.1086718:
:...ALT.12 > 0.9662921: F2 (4.7)
ALT.12 <= 0.9662921:
:...ALT.12 <= 0: F2 (7.8/1.9)
ALT.12 > 0:
:...ALT.24 <= 0.1123596:
:...ALT.12 > 0.8202247: F4 (3.1/0.7)
: ALT.12 <= 0.8202247:
: :...WBC <= 0.3774973: F4 (4/0.8)
: WBC > 0.3774973: F2 (9.1/0.9)
ALT.24 > 0.1123596:
:...ALT.36 > 0.9101124:
:...ALT.4 <= 0.5505618: F4 (6.1/0.4)
: ALT.4 > 0.5505618: F1 (3/0.4)
ALT.36 <= 0.9101124:
:...RNA.Base > 0.9340658:
:...RBC <= 0.2451413: F1 (2)
: RBC > 0.2451413: F2 (4.8/0.3)
RNA.Base <= 0.9340658:
:...RNA.Base > 0.8605266: F4 (9.1/3.2)
RNA.Base <= 0.8605266:
:...RNA.4 <= 0.3554743:
:...ALT.36 <= 0.3820225:
: :...Plat <= 0.1787922: F3 (2.4/0.9)
: : Plat > 0.1787922:
: : :...BMI <= 0.6153846: F4 (2.6/1)
: : BMI > 0.6153846: F1 (9/2.4)
: ALT.36 > 0.3820225:
: :...WBC <= 0.5919868: F2 (14.4/1.7)
: WBC > 0.5919868:
: :...ALT.36 <= 0.494382: F2 (3.4/1)
: ALT.36 > 0.494382: F3 (5.1/2.3)
RNA.4 > 0.3554743:
:...Plat > 0.5815318:
:...BMI > 0.9230769: F1 (2.4/1.1)
: BMI <= 0.9230769:
: :...AST.1 > 0.5617977:
: :...Age <= 0.7931035: F3 (7.9/0.8)
: : Age > 0.7931035: F1 (2.4/0.8)
: AST.1 <= 0.5617977:
: :...Age > 0.8965517: F2 (3/0.4)
: Age <= 0.8965517: [S6]
Plat <= 0.5815318:
:...RNA.Base <= 0.08317132: F1 (3)
RNA.Base > 0.08317132:
:...ALT.1 > 0.8202247:
:...Plat <= 0.3123768: F1 (5/1.4)
: Plat > 0.3123768: F3 (3.4)
ALT.1 <= 0.8202247:
:...Plat <= 0.1174064: [S7]
Plat > 0.1174064:
:...RNA.Base > 0.7378607: [S8]
RNA.Base <= 0.7378607: [S9]
SubTree [S1]
ALT.after.24.w > 0.6956522: F2 (5.6/0.5)
ALT.after.24.w <= 0.6956522:
:...ALT.36 <= 0.3146068: F2 (5.2/1.3)
ALT.36 > 0.3146068: F1 (3.5)
SubTree [S2]
RNA.Base <= 0.3972525: F3 (3.6)
RNA.Base > 0.3972525: F2 (2.7/0.8)
SubTree [S3]
AST.1 <= 0.5393258: F4 (8.1/1.8)
AST.1 > 0.5393258: F3 (3.8)
SubTree [S4]
ALT.48 <= 0.6179775: F4 (2.4/0.4)
ALT.48 > 0.6179775: F3 (4.1)
SubTree [S5]
RNA.4 > 0.9045269: F3 (3.4/1.7)
RNA.4 <= 0.9045269:
:...RNA.Base > 0.7981858: F1 (4.6/1.7)
RNA.Base <= 0.7981858:
:...RNA.4 <= 0.4413278: F1 (4.1)
RNA.4 > 0.4413278:
:...RNA.4 <= 0.8165855: F2 (12.7/1.9)
RNA.4 > 0.8165855: F1 (3.5)
SubTree [S6]
ALT.1 <= 0.3483146: F2 (3.3/0.6)
ALT.1 > 0.3483146: F1 (5.3)
SubTree [S7]
ALT.1 <= 0.5280899: F4 (7.2)
ALT.1 > 0.5280899: F3 (3.7)
SubTree [S8]
ALT.36 <= 0.1797753: F3 (2.5)
ALT.36 > 0.1797753: F1 (6.2)
SubTree [S9]
ALT.48 <= 0.2022472: F4 (4.4)
ALT.48 > 0.2022472:
:...ALT.36 <= 0.4269663:
:...ALT.1 <= 0.4157303: F3 (3.3)
: ALT.1 > 0.4157303: F4 (3.5/0.5)
ALT.36 > 0.4269663:
:...WBC <= 0.8261251: F3 (11.3/1)
WBC > 0.8261251: F1 (2.9)
----- Trial 14: -----
Decision tree:
BMI > 0.5384616:
:...Plat > 0.9696817: F2 (11/2.5)
: Plat <= 0.9696817:
: :...WBC <= 0.04522503:
: :...ALT.48 > 0.752809: F3 (3.3/0.7)
: : ALT.48 <= 0.752809:
: : :...RNA.Base <= 0.55075: F1 (10.1/1.7)
: : RNA.Base > 0.55075: F2 (2.5/0.4)
: WBC > 0.04522503:
: :...WBC > 0.9728869: F3 (10.1/2.6)
: WBC <= 0.9728869:
: :...ALT.12 <= 0.4269663:
: :...BMI > 0.9230769:
: : :...ALT.36 > 0.8202247: F1 (3.9/1.3)
: : : ALT.36 <= 0.8202247:
: : : :...RNA.4 <= 0.01188473: F2 (2.4)
: : : RNA.4 > 0.01188473:
: : : :...RBC > 0.6150659: F3 (10.2/3.1)
: : : RBC <= 0.6150659:
: : : :...ALT.48 <= 0.5168539: F3 (3.5/0.4)
: : : ALT.48 > 0.5168539: F4 (6.4)
: : BMI <= 0.9230769:
: : :...ALT.12 <= 0.01123596:
: : :...ALT.after.24.w <= 0.7391304: F1 (7.2/0.9)
: : : ALT.after.24.w > 0.7391304: F2 (3.8)
: : ALT.12 > 0.01123596:
: : :...ALT.12 <= 0.06741573:
: : :...ALT.1 > 0.6067415: F3 (7.4/0.6)
: : : ALT.1 <= 0.6067415:
: : : :...Age <= 0.3448276: F4 (5.5)
: : : Age > 0.3448276: F2 (4/0.6)
: : ALT.12 > 0.06741573:
: : :...AST.1 <= 0.1011236:
: : :...Plat <= 0.7116845: F4 (4.5/0.7)
: : : Plat > 0.7116845: F2 (2.1/0.4)
: : AST.1 > 0.1011236:
: : :...BMI <= 0.6153846:
: : :...AST.1 <= 0.4719101: F1 (8.4/3.3)
: : : AST.1 > 0.4719101:
: : : :...Age <= 0.1034483: F4 (2.5/0.3)
: : : Age > 0.1034483:
: : : :...ALT.12 <= 0.3146068: F2 (8.8/1.5)
: : : ALT.12 > 0.3146068: F3 (2.5/0.4)
: : BMI > 0.6153846:
: : :...Plat > 0.8451791:
: : :...RBC > 0.8593162: F1 (2.1)
: : : RBC <= 0.8593162:
: : : :...Age <= 0.06896552: F3 (3.6)
: : : Age > 0.06896552:
: : : :...WBC <= 0.5300769: F2 (5.3)
: : : WBC > 0.5300769: F3 (2.5)
: : Plat <= 0.8451791:
: : :...ALT.12 <= 0.1797753:
: : :...ALT.4 <= 0.3483146: F1 (8.6/1.1)
: : : ALT.4 > 0.3483146:
: : : :...Plat <= 0.2042922: F4 (4.7)
: : : Plat > 0.2042922:
: : : :...ALT.12 <= 0.1011236: F4 (5/2.3)
: : : ALT.12 > 0.1011236: F1 (5/1.2)
: : ALT.12 > 0.1797753:
: : :...ALT.48 > 0.6179775:
: : :...AST.1 <= 0.7977528: F1 (12.8)
: : : AST.1 > 0.7977528:
: : : :...Age <= 0.4827586: F1 (2.7)
: : : Age > 0.4827586: F3 (3.7)
: : ALT.48 <= 0.6179775:
: : :...BMI <= 0.6923077: F1 (4.4/2.1)
: : BMI > 0.6923077:
: : :...AST.1 > 0.8876405: F4 (2.6/0.4)
: : AST.1 <= 0.8876405:
: : :...Plat <= 0.4272729: [S1]
: : Plat > 0.4272729: [S2]
: ALT.12 > 0.4269663:
: :...ALT.4 > 0.9325843: F2 (10.2/1.4)
: ALT.4 <= 0.9325843:
: :...ALT.after.24.w > 0.5652174:
: :...AST.1 <= 0.1348315:
: : :...ALT.48 <= 0.5168539: F1 (9.1)
: : : ALT.48 > 0.5168539: F3 (4.2/1.2)
: : AST.1 > 0.1348315:
: : :...BMI > 0.9230769:
: : :...ALT.36 <= 0.7865168: F1 (4.5/2)
: : : ALT.36 > 0.7865168: F2 (3.7)
: : BMI <= 0.9230769:
: : :...AST.1 > 0.6292135:
: : :...RNA.4 <= 0.7352223: F4 (14.5/2.3)
: : : RNA.4 > 0.7352223: F1 (6.7/1)
: : AST.1 <= 0.6292135:
: : :...ALT.24 > 0.8539326:
: : :...ALT.4 <= 0.4269663: F3 (2.1)
: : : ALT.4 > 0.4269663: F4 (4.5)
: : ALT.24 <= 0.8539326:
: : :...RNA.Base > 0.7414416: F4 (9/2.4)
: : RNA.Base <= 0.7414416:
: : :...ALT.24 > 0.5505618: F2 (8.8)
: : ALT.24 <= 0.5505618:
: : :...ALT.24 > 0.3370787: F4 (7.3/2.4)
: : ALT.24 <= 0.3370787:
: : :...RBC <= 0.2715908: F4 (3.3)
: : RBC > 0.2715908: F2 (8.6/1.2)
: ALT.after.24.w <= 0.5652174:
: :...BMI > 0.9230769:
: :...RBC <= 0.1875362: F2 (3.3)
: : RBC > 0.1875362:
: : :...WBC <= 0.7847421: F1 (10.3/2.6)
: : WBC > 0.7847421: F4 (6.5/0.5)
: BMI <= 0.9230769:
: :...ALT.24 > 0.6741573:
: :...ALT.1 > 0.8426966: F3 (3.7)
: : ALT.1 <= 0.8426966:
: : :...ALT.after.24.w <= 0.3478261:
: : :...ALT.48 <= 0.2921348:
: : : :...Age <= 0.6206896: F3 (5.7/1)
: : : : Age > 0.6206896: F2 (4/0.6)
: : : ALT.48 > 0.2921348:
: : : :...Plat <= 0.2626282: F2 (4.8/0.8)
: : : Plat > 0.2626282: F4 (11.6/2.4)
: : ALT.after.24.w > 0.3478261:
: : :...RBC > 0.3744802: F2 (9.7/0.6)
: : RBC <= 0.3744802:
: : :...RNA.Base <= 0.6028808: F3 (3/0.3)
: : RNA.Base > 0.6028808: F2 (2.9)
: ALT.24 <= 0.6741573:
: :...ALT.4 > 0.6966292:
: :...RNA.Base > 0.7967063: F2 (3)
: : RNA.Base <= 0.7967063:
: : :...ALT.after.24.w > 0.4347826: F2 (2.6/0.9)
: : ALT.after.24.w <= 0.4347826:
: : :...ALT.12 <= 0.5393258: F1 (3.5)
: : ALT.12 > 0.5393258: F3 (5.3/1.7)
: ALT.4 <= 0.6966292:
: :...ALT.12 <= 0.5280899:
: :...RBC <= 0.9579428: F4 (6.5/0.8)
: : RBC > 0.9579428: F2 (2.2)
: ALT.12 > 0.5280899:
: :...ALT.12 <= 0.6179775: F3 (5.6)
: ALT.12 > 0.6179775:
: :...ALT.after.24.w > 0.4347826:
: :...RBC <= 0.5191805: F4 (2.4)
: : RBC > 0.5191805: F1 (3.4/0.9)
: ALT.after.24.w <= 0.4347826:
: :...ALT.4 <= 0.08988764: F1 (2.3/0.8)
: ALT.4 > 0.08988764:
: :...AST.1 > 0.5280899:
: :...WBC <= 0.4117453: F2 (3.6/1.5)
: : WBC > 0.4117453: F4 (3.4/0.1)
: AST.1 <= 0.5280899:
: :...Plat > 0.7514294: F2 (2.4)
: Plat <= 0.7514294: [S3]
BMI <= 0.5384616:
:...AST.1 > 0.9662921:
:...Age <= 0.1724138: F4 (3.7/1.3)
: Age > 0.1724138:
: :...RBC <= 0.1682464: F3 (3)
: RBC > 0.1682464: F2 (7.3/1.8)
AST.1 <= 0.9662921:
:...ALT.24 > 0.9662921:
:...ALT.48 <= 0.5842696: F4 (9.5/1.8)
: ALT.48 > 0.5842696: F1 (7.5/0.8)
ALT.24 <= 0.9662921:
:...ALT.48 > 0.9438202:
:...RNA.Base <= 0.7217867:
: :...RNA.4 <= 0.1260837: F4 (3.8/1.7)
: : RNA.4 > 0.1260837: F2 (12.9/1)
: RNA.Base > 0.7217867:
: :...ALT.48 > 0.988764: F3 (3)
: ALT.48 <= 0.988764:
: :...ALT.24 <= 0.1573034: F1 (2.6/1.3)
: ALT.24 > 0.1573034: F4 (5.8)
ALT.48 <= 0.9438202:
:...AST.1 <= 0.02247191:
:...WBC <= 0.1493963: F3 (2.8/1.4)
: WBC > 0.1493963:
: :...RBC > 0.7443614: F1 (2.3/0.4)
: RBC <= 0.7443614:
: :...ALT.36 <= 0.7303371: F4 (10.7/1.9)
: ALT.36 > 0.7303371: F1 (3.9/0.6)
AST.1 > 0.02247191:
:...RNA.Base > 0.9278438:
:...Age > 0.8275862:
: :...ALT.4 <= 0.6966292: F1 (2.8/0.8)
: : ALT.4 > 0.6966292: F4 (5.6/0.6)
: Age <= 0.8275862:
: :...RNA.4 <= 0.1535603: F1 (3.5)
: RNA.4 > 0.1535603:
: :...RNA.Base <= 0.9311683: F1 (3)
: RNA.Base > 0.9311683:
: :...Plat <= 0.2732014: F1 (5.5/1.9)
: Plat > 0.2732014: F3 (15.1/3.9)
RNA.Base <= 0.9278438:
:...ALT.12 > 0.8876405:
:...BMI > 0.3846154:
: :...AST.1 <= 0.741573: F3 (7)
: : AST.1 > 0.741573: F1 (2.3/0.3)
: BMI <= 0.3846154:
: :...ALT.48 <= 0.3707865:
: :...BMI <= 0.1538462: F4 (6.8/1.6)
: : BMI > 0.1538462: F1 (4.4)
: ALT.48 > 0.3707865:
: :...Plat > 0.5267552:
: :...Plat <= 0.7677125: F2 (5.4/1.7)
: : Plat > 0.7677125: F4 (5.8/1.7)
: Plat <= 0.5267552:
: :...ALT.36 <= 0.03370786: F4 (2)
: ALT.36 > 0.03370786:
: :...RNA.4 <= 0.2149778: F1 (2.1/0.6)
: RNA.4 > 0.2149778:
: :...RNA.4 <= 0.4249694: F3 (4.9)
: RNA.4 > 0.4249694:
: :...ALT.48 <= 0.4719101: F3 (4.5)
: ALT.48 > 0.4719101: F1 (3.5/0.6)
ALT.12 <= 0.8876405:
:...Age > 0.8275862:
:...WBC <= 0.0672887: F3 (7.7/1.8)
: WBC > 0.0672887:
: :...ALT.1 > 0.8202247:
: :...ALT.24 > 0.741573: F4 (2.5)
: : ALT.24 <= 0.741573:
: : :...ALT.48 <= 0.2022472: F1 (2.4/0.8)
: : ALT.48 > 0.2022472: F3 (8.1/0.9)
: ALT.1 <= 0.8202247:
: :...RNA.4 > 0.9263691: F3 (4/0.7)
: RNA.4 <= 0.9263691:
: :...ALT.4 > 0.5168539:
: :...ALT.12 <= 0.1235955: F2 (2.7/1)
: : ALT.12 > 0.1235955: F1 (19.2/3.9)
: ALT.4 <= 0.5168539:
: :...ALT.4 > 0.3370787: F2 (9.1/1.7)
: ALT.4 <= 0.3370787: [S4]
Age <= 0.8275862:
:...BMI <= 0.2307692:
:...Age > 0.4482759:
: :...ALT.48 > 0.6741573:
: : :...RNA.Base <= 0.7440451: F2 (15.2/4.8)
: : : RNA.Base > 0.7440451: F3 (3.6/1.1)
: : ALT.48 <= 0.6741573:
: : :...WBC <= 0.1259056: F1 (4.3/1.5)
: : WBC > 0.1259056:
: : :...RNA.4 > 0.9067978: F4 (6.5/0.4)
: : RNA.4 <= 0.9067978:
: : :...ALT.48 <= 0.2247191: F3 (9.1)
: : ALT.48 > 0.2247191:
: : :...ALT.24 <= 0.5393258: [S5]
: : ALT.24 > 0.5393258: [S6]
: Age <= 0.4482759:
: :...Plat > 0.9235899: F2 (6.7/1.9)
: Plat <= 0.9235899:
: :...Plat > 0.769451:
: :...Plat <= 0.8451791: F3 (5.3/0.6)
: : Plat > 0.8451791: F1 (9.3/1.4)
: Plat <= 0.769451:
: :...RBC <= 0.09161426: F2 (5.4/0.5)
: RBC > 0.09161426:
: :...ALT.36 <= 0.1235955:
: :...RNA.4 <= 0.3351882: F3 (4.2)
: : RNA.4 > 0.3351882: F2 (5.4/1.6)
: ALT.36 > 0.1235955:
: :...BMI > 0.1538462:
: :...WBC <= 0.2250274: F3 (3.1/1.8)
: : WBC > 0.2250274: F1 (12.9/2.3)
: BMI <= 0.1538462:
: :...Plat <= 0.478745: [S7]
: Plat > 0.478745:
: :...BMI <= 0.07692308: [S8]
: BMI > 0.07692308: [S9]
BMI > 0.2307692:
:...ALT.after.24.w <= 0.2608696:
:...ALT.24 > 0.8539326: F2 (6/0.4)
: ALT.24 <= 0.8539326:
: :...WBC > 0.9610319: F2 (3.8)
: WBC <= 0.9610319:
: :...ALT.after.24.w <= 0: F3 (2.6/0.3)
: ALT.after.24.w > 0:
: :...ALT.4 > 0.9213483: F3 (3.6/1.1)
: ALT.4 <= 0.9213483:
: :...Plat > 0.6930709: F4 (13.3/1)
: Plat <= 0.6930709: [S10]
ALT.after.24.w > 0.2608696:
:...ALT.4 <= 0.1235955:
:...RNA.Base <= 0.2562629: F1 (3.5/0.8)
: RNA.Base > 0.2562629: F3 (6.8/0.6)
ALT.4 > 0.1235955:
:...RNA.4 <= 0.04328915:
:...ALT.12 <= 0.4606742: F1 (4.9)
: ALT.12 > 0.4606742: F2 (3.6/0.4)
RNA.4 > 0.04328915:
:...WBC <= 0.01317234: F2 (3.6)
WBC > 0.01317234:
:...AST.1 <= 0.05617978:
:...ALT.1 <= 0.5280899: F2 (5.1)
: ALT.1 > 0.5280899: F3 (3.1/1.3)
AST.1 > 0.05617978:
:...ALT.48 > 0.8876405:
:...RBC <= 0.4879217: F3 (3.8/0.6)
: RBC > 0.4879217: F1 (3.8)
ALT.48 <= 0.8876405:
:...Plat > 0.8375658: F1 (8.7/3)
Plat <= 0.8375658:
:...ALT.1 <= 0.258427: [S11]
ALT.1 > 0.258427:
:...Age <= 0.4137931: [S12]
Age > 0.4137931: [S13]
SubTree [S1]
AST.1 <= 0.4831461: F3 (4.8/0.9)
AST.1 > 0.4831461: F2 (5.1/0.8)
SubTree [S2]
ALT.after.24.w <= 0.4347826: F3 (4.8/1)
ALT.after.24.w > 0.4347826: F1 (7.2/2)
SubTree [S3]
ALT.24 <= 0.3483146: F3 (4.8)
ALT.24 > 0.3483146: F2 (3/0.7)
SubTree [S4]
ALT.after.24.w > 0.7391304: F1 (4.9/2.1)
ALT.after.24.w <= 0.7391304:
:...Plat <= 0.8184652: F4 (7.4/0.2)
Plat > 0.8184652: F1 (2.3/0.3)
SubTree [S5]
RNA.4 <= 0.373249: F4 (4.9/1.1)
RNA.4 > 0.373249: F3 (7.5)
SubTree [S6]
ALT.1 <= 0.494382: F4 (6.9/0.9)
ALT.1 > 0.494382: F2 (3)
SubTree [S7]
ALT.24 <= 0.5505618: F1 (10.9/2.6)
ALT.24 > 0.5505618:
:...RNA.4 <= 0.524624: F4 (4.4)
RNA.4 > 0.524624: F2 (3.3/1.3)
SubTree [S8]
ALT.1 <= 0.5393258: F3 (5.9/0.7)
ALT.1 > 0.5393258: F4 (2.3)
SubTree [S9]
RNA.4 <= 0.4438475: F2 (4.5/1.7)
RNA.4 > 0.4438475: F4 (3.2)
SubTree [S10]
ALT.1 <= 0.3820225: F4 (10.9/2.5)
ALT.1 > 0.3820225: F2 (7.2/2)
SubTree [S11]
BMI > 0.4615385: F3 (2.5/0.7)
BMI <= 0.4615385:
:...ALT.after.24.w <= 0.4347826: F4 (4.7)
ALT.after.24.w > 0.4347826:
:...ALT.36 <= 0.4494382: F4 (4.6)
ALT.36 > 0.4494382: F3 (8.4/0.8)
SubTree [S12]
Age > 0.2413793: F2 (10.4/3.1)
Age <= 0.2413793:
:...AST.1 <= 0.7752809: F4 (12.1/2.4)
AST.1 > 0.7752809: F1 (4.2/1.3)
SubTree [S13]
ALT.48 <= 0.1573034:
:...Age <= 0.5862069: F4 (3/0.8)
: Age > 0.5862069: F3 (4/0.5)
ALT.48 > 0.1573034:
:...AST.1 <= 0.4719101: F1 (3.3/0.6)
AST.1 > 0.4719101: F4 (14.1/3.1)
----- Trial 15: -----
Decision tree:
BMI <= 0.5384616:
:...ALT.12 > 0.9325843:
: :...ALT.24 <= 0.1123596: F1 (3.3/0.3)
: : ALT.24 > 0.1123596:
: : :...ALT.after.24.w > 0.5217391:
: : :...ALT.24 <= 0.6629214: F4 (9.9/2.2)
: : : ALT.24 > 0.6629214: F3 (5.9/0.9)
: : ALT.after.24.w <= 0.5217391:
: : :...ALT.12 > 0.9775281: F3 (4.5/3)
: : ALT.12 <= 0.9775281:
: : :...ALT.24 <= 0.6741573: F3 (10.2/1.6)
: : ALT.24 > 0.6741573: F1 (2.5)
: ALT.12 <= 0.9325843:
: :...AST.1 > 0.7640449:
: :...RNA.Base > 0.9233087: F3 (6)
: : RNA.Base <= 0.9233087:
: : :...ALT.1 <= 0.05617978:
: : :...RBC <= 0.6272686: F3 (4.1)
: : : RBC > 0.6272686: F1 (2.4)
: : ALT.1 > 0.05617978:
: : :...ALT.48 > 0.4719101:
: : :...RNA.4 <= 0.831099:
: : : :...RBC <= 0.4102663:
: : : : :...ALT.48 <= 0.9101124: F3 (12/2.7)
: : : : : ALT.48 > 0.9101124: F2 (3.8)
: : : : RBC > 0.4102663:
: : : : :...Plat <= 0.9670366: F2 (21/4.5)
: : : : Plat > 0.9670366: F4 (2.1/0.7)
: : : RNA.4 > 0.831099:
: : : :...WBC > 0.6020856: F3 (2.3)
: : : WBC <= 0.6020856:
: : : :...ALT.1 <= 0.4719101: F4 (2)
: : : ALT.1 > 0.4719101: F1 (4.8)
: : ALT.48 <= 0.4719101:
: : :...WBC > 0.7139407:
: : :...RBC <= 0.2597441: F3 (2.4/0.9)
: : : RBC > 0.2597441: F4 (12.2/0.6)
: : WBC <= 0.7139407:
: : :...ALT.36 > 0.7977528: F3 (5/1.2)
: : ALT.36 <= 0.7977528:
: : :...BMI <= 0: F1 (2.8)
: : BMI > 0:
: : :...ALT.24 <= 0.4269663:
: : :...Plat <= 0.4799589: F2 (5.6/1.1)
: : : Plat > 0.4799589: F1 (4.8/0.8)
: : ALT.24 > 0.4269663:
: : :...ALT.4 <= 0.5393258: F2 (7.6/1.3)
: : ALT.4 > 0.5393258: F4 (6/0.8)
: AST.1 <= 0.7640449:
: :...ALT.36 > 0.9213483:
: :...ALT.36 <= 0.9325843: F2 (5.8/1.2)
: : ALT.36 > 0.9325843:
: : :...ALT.24 <= 0.3707865:
: : :...AST.1 <= 0.4831461: F1 (5.2/0.9)
: : : AST.1 > 0.4831461: F2 (2.6/0.3)
: : ALT.24 > 0.3707865:
: : :...ALT.1 <= 0.3033708: F1 (6.6/1.8)
: : ALT.1 > 0.3033708:
: : :...ALT.after.24.w <= 0.5217391: F1 (5/1.7)
: : ALT.after.24.w > 0.5217391: F4 (5.1/0.3)
: ALT.36 <= 0.9213483:
: :...WBC <= 0.1086718:
: :...ALT.after.24.w <= 0.173913: F2 (8.6/1.3)
: : ALT.after.24.w > 0.173913:
: : :...ALT.12 <= 0.1235955: F2 (3.8)
: : ALT.12 > 0.1235955:
: : :...RNA.4 > 0.7847043:
: : :...ALT.12 <= 0.7640449: F2 (6.4/1.4)
: : : ALT.12 > 0.7640449: F3 (2.4/0.6)
: : RNA.4 <= 0.7847043:
: : :...Age <= 0.3448276:
: : :...ALT.24 <= 0.6179775: F4 (7.2/1)
: : : ALT.24 > 0.6179775: F1 (4.1/1)
: : Age > 0.3448276:
: : :...ALT.4 <= 0.5505618: F3 (11.4)
: : ALT.4 > 0.5505618: F1 (3.3/0.6)
: WBC > 0.1086718:
: :...AST.1 <= 0.02247191:
: :...ALT.after.24.w <= 0.1304348: F1 (3.8/1.2)
: : ALT.after.24.w > 0.1304348:
: : :...RNA.Base <= 0.04202569: F1 (2.6)
: : RNA.Base > 0.04202569: F4 (11.2/2.1)
: AST.1 > 0.02247191:
: :...ALT.24 <= 0.04494382:
: :...RNA.Base <= 0.7967063:
: : :...ALT.12 <= 0.6179775: F4 (4.1/0.9)
: : : ALT.12 > 0.6179775: F3 (2.4/0.5)
: : RNA.Base > 0.7967063:
: : :...RNA.Base <= 0.9266616: F3 (8.3/0.9)
: : RNA.Base > 0.9266616: F1 (2)
: ALT.24 > 0.04494382:
: :...RBC > 0.8862565:
: :...RNA.Base <= 0.1472947: F3 (5.2/1)
: : RNA.Base > 0.1472947:
: : :...ALT.36 > 0.494382:
: : :...ALT.48 <= 0.4157303: F3 (4.3/1.4)
: : : ALT.48 > 0.4157303: F2 (4.5)
: : ALT.36 <= 0.494382:
: : :...ALT.4 > 0.6179775: F4 (2)
: : ALT.4 <= 0.6179775:
: : :...WBC <= 0.3274424: F1 (2.4)
: : WBC > 0.3274424: F2 (4.2/0.8)
: RBC <= 0.8862565:
: :...BMI <= 0.3076923:
: :...Age > 0.862069:
: : :...WBC > 0.7708013: F4 (5.9)
: : : WBC <= 0.7708013:
: : : :...ALT.24 <= 0.2921348: F2 (2)
: : : ALT.24 > 0.2921348:
: : : :...ALT.4 <= 0.4719101: F4 (4/1)
: : : ALT.4 > 0.4719101: F1 (4.9)
: : Age <= 0.862069:
: : :...Age <= 0.137931:
: : :...RNA.Base <= 0.05632871: F3 (2.8)
: : : RNA.Base > 0.05632871:
: : : :...Age <= 0.06896552:
: : : :...BMI <= 0.1538462: F4 (9.6/1.6)
: : : : BMI > 0.1538462: F1 (7/1.9)
: : : Age > 0.06896552:
: : : :...ALT.24 <= 0.6067415: F3 (2.7/0.7)
: : : ALT.24 > 0.6067415: F1 (6.7/1.3)
: : Age > 0.137931:
: : :...ALT.1 <= 0.4382023:
: : :...Plat <= 0.1579456:
: : : :...ALT.24 <= 0.4719101: F2 (2.2)
: : : : ALT.24 > 0.4719101: [S1]
: : : Plat > 0.1579456:
: : : :...ALT.after.24.w > 0.7826087:
: : : :...ALT.1 <= 0.1685393: F3 (3.8/0.5)
: : : : ALT.1 > 0.1685393: [S2]
: : : ALT.after.24.w <= 0.7826087: [S3]
: : ALT.1 > 0.4382023:
: : :...Plat <= 0.2414594:
: : :...ALT.12 <= 0.6741573: F4 (10.7/1.9)
: : : ALT.12 > 0.6741573: F2 (3.6/0.9)
: : Plat > 0.2414594:
: : :...ALT.after.24.w <= 0.173913:
: : :...AST.1 > 0.6067415: F1 (3.9)
: : : AST.1 <= 0.6067415: [S4]
: : ALT.after.24.w > 0.173913:
: : :...ALT.12 > 0.5842696: F3 (7/1)
: : ALT.12 <= 0.5842696:
: : :...Age > 0.7241379: F3 (4.9/1.1)
: : Age <= 0.7241379: [S5]
: BMI > 0.3076923:
: :...RNA.Base <= 0.06876256: F2 (6.9/1.9)
: RNA.Base > 0.06876256:
: :...ALT.24 > 0.6629214:
: :...ALT.1 <= 0.4157303:
: : :...Age > 0.862069: F3 (3.4/0.9)
: : : Age <= 0.862069:
: : : :...ALT.48 > 0.741573: F4 (2.3)
: : : ALT.48 <= 0.741573:
: : : :...ALT.12 <= 0.1235955: F4 (2.3/0.8)
: : : ALT.12 > 0.1235955: F2 (10.2)
: : ALT.1 > 0.4157303:
: : :...ALT.after.24.w <= 0.3478261: F4 (7.3/1.5)
: : ALT.after.24.w > 0.3478261:
: : :...ALT.48 <= 0.3595506: F1 (6.2)
: : ALT.48 > 0.3595506:
: : :...ALT.48 <= 0.8651685: F4 (6.5/0.9)
: : ALT.48 > 0.8651685: F1 (2.3)
: ALT.24 <= 0.6629214:
: :...ALT.1 > 0.6516854:
: :...ALT.36 <= 0.08988764: F4 (2.2/0.3)
: : ALT.36 > 0.08988764:
: : :...BMI > 0.4615385: F3 (5.9/0.3)
: : BMI <= 0.4615385:
: : :...Age <= 0.3793103: F3 (3.3)
: : Age > 0.3793103: F1 (5.7/1.2)
: ALT.1 <= 0.6516854:
: :...Plat <= 0.1329252:
: :...ALT.4 <= 0.752809: F4 (3.1/1.2)
: : ALT.4 > 0.752809: F3 (7.6)
: Plat > 0.1329252:
: :...ALT.12 <= 0.1685393: F4 (6.4/0.9)
: ALT.12 > 0.1685393:
: :...Plat <= 0.5898195:
: :...BMI <= 0.3846154: [S6]
: : BMI > 0.3846154: [S7]
: Plat > 0.5898195:
: :...BMI > 0.4615385: F3 (2)
: BMI <= 0.4615385: [S8]
BMI > 0.5384616:
:...ALT.after.24.w > 0.9130435:
:...BMI > 0.9230769: F2 (3.6)
: BMI <= 0.9230769:
: :...AST.1 <= 0.2247191: F1 (6.6/1.9)
: AST.1 > 0.2247191:
: :...ALT.48 <= 0.4719101: F3 (8.5)
: ALT.48 > 0.4719101:
: :...ALT.after.24.w <= 0.9565217: F3 (5.4/2.2)
: ALT.after.24.w > 0.9565217:
: :...WBC <= 0.2090011: F2 (3.1/1.1)
: WBC > 0.2090011: F4 (5/2.4)
ALT.after.24.w <= 0.9130435:
:...ALT.after.24.w > 0.8260869:
:...ALT.4 <= 0.3370787:
: :...ALT.1 > 0.8314607: F2 (2.1/0.4)
: : ALT.1 <= 0.8314607:
: : :...ALT.48 <= 0.3146068: F1 (4.7/1.7)
: : ALT.48 > 0.3146068: F4 (10.6/0.3)
: ALT.4 > 0.3370787:
: :...RNA.4 > 0.9194365: F3 (2.9)
: RNA.4 <= 0.9194365:
: :...ALT.1 <= 0.2808989: F1 (6.6/0.5)
: ALT.1 > 0.2808989:
: :...ALT.after.24.w <= 0.8695652:
: :...ALT.24 <= 0.3595506: F2 (2.4)
: : ALT.24 > 0.3595506: F4 (4.4/1.4)
: ALT.after.24.w > 0.8695652:
: :...RBC <= 0.3201445: F1 (3.1/0.6)
: RBC > 0.3201445: F3 (3.5/1.6)
ALT.after.24.w <= 0.8260869:
:...ALT.after.24.w <= 0.04347826:
:...ALT.4 <= 0.2134831: F1 (6.8/2.9)
: ALT.4 > 0.2134831:
: :...Plat <= 0.2486081:
: :...ALT.36 <= 0.2359551: F1 (3.4/1)
: : ALT.36 > 0.2359551:
: : :...WBC <= 0.5443469: F4 (4.3/1.3)
: : WBC > 0.5443469: F2 (3.4/0.4)
: Plat > 0.2486081:
: :...WBC <= 0.7568606: F3 (15.2/1)
: WBC > 0.7568606:
: :...Age <= 0.3103448: F2 (3)
: Age > 0.3103448: F3 (4.3/2)
ALT.after.24.w > 0.04347826:
:...Plat > 0.9565158:
:...RNA.Base <= 0.0862186: F4 (4.6/1)
: RNA.Base > 0.0862186: F2 (6.4)
Plat <= 0.9565158:
:...ALT.1 <= 0.1797753:
:...ALT.1 <= 0.03370786: F2 (7.4/1.5)
: ALT.1 > 0.03370786:
: :...RNA.Base > 0.3271777:
: :...ALT.12 <= 0.5393258:
: : :...RBC <= 0.8901707: F3 (10/5.1)
: : : RBC > 0.8901707: F1 (4.5/0.9)
: : ALT.12 > 0.5393258:
: : :...Plat <= 0.5656908: F2 (7.3/0.5)
: : Plat > 0.5656908: F1 (2.1)
: RNA.Base <= 0.3271777:
: :...BMI > 0.7692308: F3 (3/0.6)
: BMI <= 0.7692308:
: :...Age > 0.6551724: F1 (5.1)
: Age <= 0.6551724:
: :...ALT.12 <= 0.2134831: F1 (3)
: ALT.12 > 0.2134831: F3 (5.3)
ALT.1 > 0.1797753:
:...AST.1 <= 0.08988764:
:...WBC > 0.5781559:
: :...ALT.24 <= 0.752809: F2 (4.7/1.1)
: : ALT.24 > 0.752809: F3 (4)
: WBC <= 0.5781559:
: :...BMI <= 0.8461539: F4 (5.7/1.1)
: BMI > 0.8461539:
: :...WBC <= 0.456202: F2 (4.2/0.6)
: WBC > 0.456202: F4 (3.1)
AST.1 > 0.08988764:
:...ALT.24 <= 0.3258427:
:...WBC > 0.9160264:
: :...ALT.12 <= 0.258427: F4 (2.5/0.6)
: : ALT.12 > 0.258427: F2 (4.9/0.4)
: WBC <= 0.9160264:
: :...Age > 0.7931035:
: :...ALT.12 <= 0.5280899: F1 (6.4/0.9)
: : ALT.12 > 0.5280899: F3 (6.1/1.3)
: Age <= 0.7931035:
: :...ALT.36 <= 0.07865169:
: :...WBC <= 0.3384193: F2 (3.4)
: : WBC > 0.3384193: F4 (3.8)
: ALT.36 > 0.07865169:
: :...AST.1 > 0.6292135:
: :...ALT.36 <= 0.2696629: F1 (3.4/0.7)
: : ALT.36 > 0.2696629: F4 (15.2/3.3)
: AST.1 <= 0.6292135:
: :...ALT.after.24.w > 0.6521739:
: :...RNA.4 <= 0.07378402: F2 (2.2)
: : RNA.4 > 0.07378402: F4 (4.8/1.1)
: ALT.after.24.w <= 0.6521739:
: :...ALT.24 > 0.247191: F3 (3.1)
: ALT.24 <= 0.247191:
: :...ALT.24 <= 0.2022472: F1 (17.8/6.8)
: ALT.24 > 0.2022472: [S9]
ALT.24 > 0.3258427:
:...ALT.4 <= 0.07865169:
:...RBC <= 0.820986: F1 (10/2.2)
: RBC > 0.820986: F3 (3.7/1.2)
ALT.4 > 0.07865169:
:...RNA.Base <= 0.1169985:
:...WBC > 0.8243688: F1 (3.3)
: WBC <= 0.8243688:
: :...ALT.after.24.w > 0.4782609: F2 (8.7)
: ALT.after.24.w <= 0.4782609:
: :...RNA.Base <= 0.0426751: F2 (3.3/0.7)
: RNA.Base > 0.0426751: F1 (2.7)
RNA.Base > 0.1169985:
:...ALT.1 <= 0.2808989:
:...Age <= 0.6551724: F4 (4/1.5)
: Age > 0.6551724: F3 (4.7)
ALT.1 > 0.2808989:
:...RNA.Base <= 0.2014179:
:...ALT.24 <= 0.5617977: F4 (2.2/0.7)
: ALT.24 > 0.5617977: F3 (8/1.8)
RNA.Base > 0.2014179:
:...RBC > 0.9284534: F4 (5.2/0.9)
RBC <= 0.9284534:
:...ALT.1 <= 0.4382023:
:...BMI > 0.9230769: F1 (2.7/1.3)
: BMI <= 0.9230769:
: :...WBC <= 0.1587267: F4 (3/0.9)
: WBC > 0.1587267: [S10]
ALT.1 > 0.4382023:
:...ALT.12 <= 0.4719101: [S11]
ALT.12 > 0.4719101: [S12]
SubTree [S1]
ALT.after.24.w <= 0.3478261: F3 (4.3)
ALT.after.24.w > 0.3478261: F1 (4.6/1.4)
SubTree [S2]
ALT.12 <= 0.494382: F4 (2.1)
ALT.12 > 0.494382: F1 (5.5/0.4)
SubTree [S3]
ALT.after.24.w <= 0.2608696: F4 (12.5/2.7)
ALT.after.24.w > 0.2608696:
:...RBC <= 0.4437039: F4 (7.7)
RBC > 0.4437039:
:...Age <= 0.4827586: F3 (6/0.6)
Age > 0.4827586:
:...ALT.48 <= 0.4157303: F4 (5.5)
ALT.48 > 0.4157303: F3 (4.1/1.4)
SubTree [S4]
RNA.4 <= 0.4994316: F2 (5.7)
RNA.4 > 0.4994316: F3 (2.8/0.5)
SubTree [S5]
ALT.12 > 0.494382: F2 (4.2)
ALT.12 <= 0.494382:
:...RNA.Base <= 0.2462527: F2 (2.1/0.6)
RNA.Base > 0.2462527: F4 (11.9/3)
SubTree [S6]
Plat <= 0.3474534: F4 (3.1/0.5)
Plat > 0.3474534: F2 (2.9)
SubTree [S7]
Age <= 0.3793103: F2 (2.9/1.2)
Age > 0.3793103: F1 (7/0.6)
SubTree [S8]
Plat > 0.8046474: F1 (7.9)
Plat <= 0.8046474:
:...ALT.24 <= 0.1910112: F1 (2.5)
ALT.24 > 0.1910112: F4 (4.7/1.4)
SubTree [S9]
AST.1 <= 0.505618: F4 (3.6/1.6)
AST.1 > 0.505618: F2 (2.2)
SubTree [S10]
RNA.4 <= 0.3106714: F4 (3.7/1)
RNA.4 > 0.3106714: F2 (17.6/0.7)
SubTree [S11]
AST.1 > 0.6404495: F2 (6.5/2.2)
AST.1 <= 0.6404495:
:...ALT.36 > 0.4044944: F1 (11.1/0.9)
ALT.36 <= 0.4044944:
:...WBC > 0.584303: F1 (3.4)
WBC <= 0.584303:
:...ALT.1 > 0.9662921: F4 (2.3)
ALT.1 <= 0.9662921:
:...ALT.4 <= 0.6179775: F3 (4.2)
ALT.4 > 0.6179775: F2 (2.3)
SubTree [S12]
ALT.4 > 0.7640449: F2 (9.7/0.7)
ALT.4 <= 0.7640449:
:...ALT.36 > 0.8314607: F2 (3)
ALT.36 <= 0.8314607:
:...ALT.48 > 0.8202247: F2 (4.8/1.6)
ALT.48 <= 0.8202247:
:...RNA.Base > 0.7414416: F4 (4.5/0.2)
RNA.Base <= 0.7414416:
:...ALT.after.24.w <= 0.1304348: F4 (2.1/0.5)
ALT.after.24.w > 0.1304348: F3 (5.8)
Evaluation on training data (968 cases):
Trial Decision Tree
----- ----------------
Size Errors
0 229 106(11.0%)
1 152 244(25.2%)
2 158 256(26.4%)
3 163 246(25.4%)
4 174 213(22.0%)
5 171 210(21.7%)
6 177 227(23.5%)
7 179 221(22.8%)
8 173 221(22.8%)
9 179 211(21.8%)
10 170 216(22.3%)
11 174 208(21.5%)
12 180 219(22.6%)
13 181 191(19.7%)
14 172 225(23.2%)
15 184 204(21.1%)
boost 0( 0.0%) <<
(a) (b) (c) (d) <-classified as
---- ---- ---- ----
235 (a): class F1
232 (b): class F2
249 (c): class F3
252 (d): class F4
Attribute usage:
100.00% Age
100.00% BMI
100.00% WBC
100.00% Plat
100.00% AST.1
100.00% ALT.1
100.00% ALT.4
100.00% ALT.12
100.00% ALT.24
100.00% ALT.36
100.00% ALT.48
100.00% ALT.after.24.w
100.00% RNA.4
99.90% RBC
99.79% RNA.Base
Time: 0.5 secs
ggplot(modelo_C5.0, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo") +
theme_bw()
# Predicciones
predicciones_C5.0 <- predict(modelo_C5.0, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_C5.0 <- caret::confusionMatrix(factor(predicciones_C5.0), factor(data_tt$BH.staging))
conf_mat_C5.0
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 23 26 29 25
F2 27 23 24 24
F3 27 23 36 25
F4 23 27 17 34
Overall Statistics
Accuracy : 0.2809
95% CI : (0.238, 0.3269)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.1998
Kappa : 0.0409
Mcnemar's Test P-Value : 0.9291
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.23000 0.23232 0.33962 0.31481
Specificity 0.74441 0.76115 0.75570 0.78033
Pos Pred Value 0.22330 0.23469 0.32432 0.33663
Neg Pred Value 0.75161 0.75873 0.76821 0.76282
Prevalence 0.24213 0.23971 0.25666 0.26150
Detection Rate 0.05569 0.05569 0.08717 0.08232
Detection Prevalence 0.24939 0.23729 0.26877 0.24455
Balanced Accuracy 0.48720 0.49673 0.54766 0.54757
stats_class_C5.0 <- data.frame(model = "C5.0",
precision = conf_mat_C5.0$overall["Accuracy"],
FN = conf_mat_C5.0$table[2,1],
FP = conf_mat_C5.0$table[1,2],
error.rate = 1 - conf_mat_C5.0$overall["Accuracy"],
kappa = conf_mat_C5.0$overall["Kappa"],
sensibilidad = mean(conf_mat_C5.0$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_C5.0$byClass[,"Specificity"]),
precisión = mean(conf_mat_C5.0$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_C5.0$byClass[,"Recall"]),
f.medida = mean(conf_mat_C5.0$byClass[,"F1"])
)
stats_class_C5.0
model precision FN FP error.rate kappa sensibilidad especificidad
Accuracy C5.0 0.2808717 27 26 0.7191283 0.0409092 0.2791902 0.7603959
precisión recuperación f.medida
Accuracy 0.2797382 0.2791902 0.2793149
Generamos el modelo J48.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- expand.grid(C = c(0.5),
M = c(5:15))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
library(RWeka)
set.seed(342)
modelo_J48 <- caret::train(BH.staging ~ ., data = data_tn,
method = "J48",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train)
modelo_J48
C4.5-like Trees
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
M Accuracy Kappa
5 0.2439154 -0.008678054
6 0.2463020 -0.005472526
7 0.2444751 -0.008009420
8 0.2425773 -0.010664342
9 0.2439496 -0.008704486
10 0.2404315 -0.013540724
11 0.2473832 -0.004165628
12 0.2378972 -0.016741267
13 0.2438370 -0.009149122
14 0.2464308 -0.005621152
15 0.2484850 -0.002877747
Tuning parameter 'C' was held constant at a value of 0.5
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were C = 0.5 and M = 15.
summary(modelo_J48$finalModel)
=== Summary ===
Correctly Classified Instances 479 49.4835 %
Incorrectly Classified Instances 489 50.5165 %
Kappa statistic 0.3264
Mean absolute error 0.3113
Root mean squared error 0.3945
Relative absolute error 83.0527 %
Root relative squared error 91.1333 %
Total Number of Instances 968
=== Confusion Matrix ===
a b c d <-- classified as
101 48 45 41 | a = F1
25 121 49 37 | b = F2
44 45 133 27 | c = F3
52 42 34 124 | d = F4
ggplot(data = modelo_J48, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo J48") +
theme_bw()
# Predicciones
predicciones_J48 <- predict(modelo_J48, newdata = data_tt, type = "raw")
# Evaluación
conf_mat_J48 <- caret::confusionMatrix(factor(predicciones_J48, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_J48
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 30 26 35 20
F2 22 26 25 32
F3 27 21 25 24
F4 21 26 21 32
Overall Statistics
Accuracy : 0.2736
95% CI : (0.2312, 0.3193)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.3049
Kappa : 0.032
Mcnemar's Test P-Value : 0.8619
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.30000 0.26263 0.23585 0.29630
Specificity 0.74121 0.74841 0.76547 0.77705
Pos Pred Value 0.27027 0.24762 0.25773 0.32000
Neg Pred Value 0.76821 0.76299 0.74367 0.75719
Prevalence 0.24213 0.23971 0.25666 0.26150
Detection Rate 0.07264 0.06295 0.06053 0.07748
Detection Prevalence 0.26877 0.25424 0.23487 0.24213
Balanced Accuracy 0.52061 0.50552 0.50066 0.53667
stats_class_J48 <- data.frame(model = "J48",
precision = conf_mat_J48$overall["Accuracy"],
FN = conf_mat_J48$table[2,1],
FP = conf_mat_J48$table[1,2],
error.rate = 1 - conf_mat_J48$overall["Accuracy"],
kappa = conf_mat_J48$overall["Kappa"],
sensibilidad = mean(conf_mat_J48$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_J48$byClass[,"Specificity"]),
precisión = mean(conf_mat_J48$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_J48$byClass[,"Recall"]),
f.medida = mean(conf_mat_J48$byClass[,"F1"])
)
stats_class_J48
model precision FN FP error.rate kappa sensibilidad especificidad
Accuracy J48 0.2736077 22 26 0.7263923 0.03197075 0.2736929 0.7580358
precisión recuperación f.medida
Accuracy 0.2739053 0.2736929 0.273315
Generamos el modelo RF.
# se recurre a validación cruzada repetida como método de validación.
# Número de particiones y repeticiones
library(ranger)
particiones <- 10
repeticiones <- 10
hiperparametros <- expand.grid(mtry = c(1:20),
min.node.size = c(4, 5, 10, 20),
splitrule = c("gini"))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_rf <- caret::train(BH.staging ~ ., data = data_tn,
method = "ranger",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train,
# Número de ?rboles ajustados
num.trees = 500)
modelo_rf
Random Forest
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
mtry min.node.size Accuracy Kappa
1 4 0.2297487 -0.02998355
1 5 0.2332862 -0.02514737
1 10 0.2280793 -0.03219106
1 20 0.2253109 -0.03617561
2 4 0.2295613 -0.02972735
2 5 0.2318001 -0.02692468
2 10 0.2294276 -0.03003206
2 20 0.2225444 -0.03936560
3 4 0.2298455 -0.02943429
3 5 0.2320326 -0.02646534
3 10 0.2335018 -0.02442988
3 20 0.2269904 -0.03320512
4 4 0.2289125 -0.03023855
4 5 0.2293341 -0.02999056
4 10 0.2306927 -0.02788597
4 20 0.2247804 -0.03613900
5 4 0.2299774 -0.02904509
5 5 0.2326193 -0.02564974
5 10 0.2297563 -0.02920285
5 20 0.2249161 -0.03572673
6 4 0.2333500 -0.02458421
6 5 0.2278571 -0.03186188
6 10 0.2323102 -0.02576764
6 20 0.2267333 -0.03313005
7 4 0.2291442 -0.03006672
7 5 0.2276058 -0.03220293
7 10 0.2319233 -0.02642248
7 20 0.2247020 -0.03612791
8 4 0.2287874 -0.03070869
8 5 0.2274944 -0.03223885
8 10 0.2268150 -0.03303392
8 20 0.2261988 -0.03401410
9 4 0.2329202 -0.02509180
9 5 0.2320224 -0.02613905
9 10 0.2252696 -0.03524420
9 20 0.2235970 -0.03746428
10 4 0.2269628 -0.03299631
10 5 0.2320433 -0.02620278
10 10 0.2276360 -0.03190889
10 20 0.2291162 -0.03000464
11 4 0.2275932 -0.03203596
11 5 0.2285925 -0.03070249
11 10 0.2290442 -0.03010397
11 20 0.2261293 -0.03392040
12 4 0.2259158 -0.03430620
12 5 0.2311451 -0.02726649
12 10 0.2243778 -0.03637218
12 20 0.2263698 -0.03364498
13 4 0.2255356 -0.03483258
13 5 0.2272603 -0.03245180
13 10 0.2251124 -0.03542073
13 20 0.2257570 -0.03452538
14 4 0.2299188 -0.02891429
14 5 0.2269512 -0.03298444
14 10 0.2260191 -0.03405275
14 20 0.2261648 -0.03393651
15 4 0.2266502 -0.03340855
15 5 0.2302695 -0.02857755
15 10 0.2265611 -0.03354132
15 20 0.2217080 -0.03978043
16 4 NaN NaN
16 5 NaN NaN
16 10 NaN NaN
16 20 NaN NaN
17 4 NaN NaN
17 5 NaN NaN
17 10 NaN NaN
17 20 NaN NaN
18 4 NaN NaN
18 5 NaN NaN
18 10 NaN NaN
18 20 NaN NaN
19 4 NaN NaN
19 5 NaN NaN
19 10 NaN NaN
19 20 NaN NaN
20 4 NaN NaN
20 5 NaN NaN
20 10 NaN NaN
20 20 NaN NaN
Tuning parameter 'splitrule' was held constant at a value of gini
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were mtry = 3, splitrule = gini
and min.node.size = 10.
summary(modelo_rf$finalModel)
Length Class Mode
predictions 968 factor numeric
num.trees 1 -none- numeric
num.independent.variables 1 -none- numeric
mtry 1 -none- numeric
min.node.size 1 -none- numeric
prediction.error 1 -none- numeric
forest 9 ranger.forest list
confusion.matrix 16 table numeric
splitrule 1 -none- character
treetype 1 -none- character
call 9 -none- call
importance.mode 1 -none- character
num.samples 1 -none- numeric
replace 1 -none- logical
xNames 15 -none- character
problemType 1 -none- character
tuneValue 3 data.frame list
obsLevels 4 -none- character
param 1 -none- list
# REPRESENTACIÓN GRÁFICA
ggplot(modelo_rf, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo RF") +
theme_bw()
# Predicciones
predicciones_rf <- predict(modelo_rf, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_rf <- caret::confusionMatrix(factor(predicciones_rf, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_rf
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 14 15 25 22
F2 24 21 23 16
F3 28 22 28 33
F4 34 41 30 37
Overall Statistics
Accuracy : 0.2421
95% CI : (0.2016, 0.2864)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.82920
Kappa : -0.0135
Mcnemar's Test P-Value : 0.01403
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.1400 0.21212 0.2642 0.34259
Specificity 0.8019 0.79936 0.7296 0.65574
Pos Pred Value 0.1842 0.25000 0.2523 0.26056
Neg Pred Value 0.7448 0.76292 0.7417 0.73801
Prevalence 0.2421 0.23971 0.2567 0.26150
Detection Rate 0.0339 0.05085 0.0678 0.08959
Detection Prevalence 0.1840 0.20339 0.2688 0.34383
Balanced Accuracy 0.4710 0.50574 0.4969 0.49917
stats_class_rf <- data.frame(model = "RF",
precision = conf_mat_rf$overall["Accuracy"],
FN = conf_mat_rf$table[2,1],
FP = conf_mat_rf$table[1,2],
error.rate = 1 - conf_mat_rf$overall["Accuracy"],
kappa = conf_mat_rf$overall["Kappa"],
sensibilidad = mean(conf_mat_rf$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_rf$byClass[,"Specificity"]),
precisión = mean(conf_mat_rf$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_rf$byClass[,"Recall"]),
f.medida = mean(conf_mat_rf$byClass[,"F1"])
)
stats_class_rf
model precision FN FP error.rate kappa sensibilidad
Accuracy RF 0.2421308 24 15 0.7578692 -0.01346912 0.2397162
especificidad precisión recuperación f.medida
Accuracy 0.7466648 0.2367565 0.2397162 0.2356659
Generamos el modelo LR.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
hiperparametros <- data.frame(parameter = "none")
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_lrqda <- caret::train(BH.staging ~ ., data = data_tn,
method = "qda",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train,
family = "binomial")
modelo_lrqda
Quadratic Discriminant Analysis
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results:
Accuracy Kappa
0.2479372 -0.003896589
summary(modelo_lrqda$finalModel)
Length Class Mode
prior 4 -none- numeric
counts 4 -none- numeric
means 60 -none- numeric
scaling 900 -none- numeric
ldet 4 -none- numeric
lev 4 -none- character
N 1 -none- numeric
call 4 -none- call
xNames 15 -none- character
problemType 1 -none- character
tuneValue 1 data.frame list
obsLevels 4 -none- character
param 1 -none- list
# Predicciones
predicciones_lrqda <- predict(modelo_lrqda, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_lrqda <- caret::confusionMatrix(factor(predicciones_rf, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_lrqda
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 14 15 25 22
F2 24 21 23 16
F3 28 22 28 33
F4 34 41 30 37
Overall Statistics
Accuracy : 0.2421
95% CI : (0.2016, 0.2864)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.82920
Kappa : -0.0135
Mcnemar's Test P-Value : 0.01403
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.1400 0.21212 0.2642 0.34259
Specificity 0.8019 0.79936 0.7296 0.65574
Pos Pred Value 0.1842 0.25000 0.2523 0.26056
Neg Pred Value 0.7448 0.76292 0.7417 0.73801
Prevalence 0.2421 0.23971 0.2567 0.26150
Detection Rate 0.0339 0.05085 0.0678 0.08959
Detection Prevalence 0.1840 0.20339 0.2688 0.34383
Balanced Accuracy 0.4710 0.50574 0.4969 0.49917
stats_class_lrqda <- data.frame(model = "lrqda",
precision = conf_mat_lrqda$overall["Accuracy"],
FN = conf_mat_lrqda$table[2,1],
FP = conf_mat_lrqda$table[1,2],
error.rate = 1 - conf_mat_lrqda$overall["Accuracy"],
kappa = conf_mat_lrqda$overall["Kappa"],
sensibilidad = mean(conf_mat_lrqda$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_lrqda$byClass[,"Specificity"]),
precisión = mean(conf_mat_lrqda$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_lrqda$byClass[,"Recall"]),
f.medida = mean(conf_mat_lrqda$byClass[,"F1"])
)
stats_class_lrqda
model precision FN FP error.rate kappa sensibilidad
Accuracy lrqda 0.2421308 24 15 0.7578692 -0.01346912 0.2397162
especificidad precisión recuperación f.medida
Accuracy 0.7466648 0.2367565 0.2397162 0.2356659
Generamos el modelo PMLR.
# Número de particiones y repeticiones
particiones <- 10
repeticiones <- 10
# hiperparametros <- data.frame(decay = c(0.01,0.1,0.3,0.5))
hiperparametros <- data.frame(decay = seq(20, 30, length.out=20))
set.seed(123)
seeds <- vector(mode = "list", length = (particiones * repeticiones) + 1)
for (i in 1:(particiones * repeticiones)) {
seeds[[i]] <- sample.int(1000, nrow(hiperparametros))
}
seeds[[(particiones * repeticiones) + 1]] <- sample.int(1000, 1)
# DEFINICIÓN DEL ENTRENAMIENTO
control_train <- trainControl(method = "repeatedcv", number = particiones,
repeats = repeticiones, seeds = seeds,
returnResamp = "final", verboseIter = FALSE,
allowParallel = TRUE)
# AJUSTE DEL MODELO
set.seed(342)
modelo_lrmulti <- caret::train(BH.staging ~ ., data = data_tn,
method = "multinom",
tuneGrid = hiperparametros,
metric = "Accuracy",
trControl = control_train,
trace = FALSE)
modelo_lrmulti
Penalized Multinomial Regression
968 samples
15 predictor
4 classes: 'F1', 'F2', 'F3', 'F4'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 10 times)
Summary of sample sizes: 871, 871, 870, 873, 872, 870, ...
Resampling results across tuning parameters:
decay Accuracy Kappa
20.00000 0.2573625 0.003020865
20.52632 0.2579843 0.003799559
21.05263 0.2586082 0.004575831
21.57895 0.2587123 0.004638957
22.10526 0.2592278 0.005294440
22.63158 0.2590184 0.004930174
23.15789 0.2595339 0.005573549
23.68421 0.2598465 0.005922589
24.21053 0.2592215 0.005008619
24.73684 0.2593267 0.005073593
25.26316 0.2583934 0.003777060
25.78947 0.2586039 0.004029124
26.31579 0.2593235 0.004925881
26.84211 0.2599442 0.005701083
27.36842 0.2595308 0.005085403
27.89474 0.2594362 0.004897840
28.42105 0.2599484 0.005520001
28.94737 0.2602609 0.005882874
29.47368 0.2601589 0.005689224
30.00000 0.2598453 0.005198410
Accuracy was used to select the optimal model using the largest value.
The final value used for the model was decay = 28.94737.
summary(modelo_lrmulti$finalModel)
Call:
nnet::multinom(formula = .outcome ~ ., data = dat, decay = param$decay,
trace = FALSE)
Coefficients:
(Intercept) Age BMI WBC RBC Plat
F2 -0.03129085 0.05274264 0.12695889 -0.018279503 -0.02953207 0.10882455
F3 0.01687985 0.01248156 0.03039447 -0.004948556 -0.02483668 -0.03270340
F4 0.03804456 -0.02744159 -0.10634897 0.090278345 0.05039170 -0.06148192
AST.1 ALT.1 ALT.4 ALT.12 ALT.24 ALT.36
F2 0.06953312 0.020087418 0.0090107548 -0.02435879 -0.065443536 -0.051388068
F3 0.04480175 -0.008900156 -0.0002367104 -0.02064086 0.007014171 0.014712012
F4 -0.08328793 0.046941342 -0.0389066404 0.03394932 -0.001542109 0.000182729
ALT.48 ALT.after.24.w RNA.Base RNA.4
F2 0.009461114 -0.095947362 -0.07970566 0.005605194
F3 0.031283434 -0.009358928 -0.01580457 0.038007149
F4 -0.028421721 0.083312526 0.11495565 -0.042092674
Std. Errors:
(Intercept) Age BMI WBC RBC Plat AST.1
F2 0.6264239 0.3048569 0.2980123 0.3176346 0.3230790 0.3221376 0.3130690
F3 0.6168716 0.3003771 0.2935871 0.3129367 0.3186251 0.3178000 0.3085623
F4 0.6162174 0.2999788 0.2931728 0.3123529 0.3186463 0.3177608 0.3083305
ALT.1 ALT.4 ALT.12 ALT.24 ALT.36 ALT.48 ALT.after.24.w
F2 0.3193254 0.3135101 0.3176041 0.3166600 0.3161883 0.3191681 0.3035584
F3 0.3147818 0.3087558 0.3129938 0.3120909 0.3114574 0.3143506 0.2989055
F4 0.3146095 0.3083820 0.3131052 0.3116741 0.3109604 0.3139938 0.2984150
RNA.Base RNA.4
F2 0.3148009 0.3078573
F3 0.3100676 0.3031987
F4 0.3096031 0.3024339
Residual Deviance: 2672.651
AIC: 2768.651
# REPRESENTACIÓN GRÁFICA
ggplot(modelo_lrmulti, highlight = TRUE) +
labs(title = "Evolución del accuracy del modelo LRmulti") +
theme_bw()
# Predicciones
predicciones_lrmulti <- predict(modelo_lrmulti, newdata = data_tt,
type = "raw")
# Evaluación
conf_mat_lrmulti <- caret::confusionMatrix(factor(predicciones_rf, levels = levels(factor(data_tt$BH.staging))),
factor(data_tt$BH.staging, levels = levels(factor(data_tt$BH.staging)))
)
conf_mat_lrmulti
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 14 15 25 22
F2 24 21 23 16
F3 28 22 28 33
F4 34 41 30 37
Overall Statistics
Accuracy : 0.2421
95% CI : (0.2016, 0.2864)
No Information Rate : 0.2615
P-Value [Acc > NIR] : 0.82920
Kappa : -0.0135
Mcnemar's Test P-Value : 0.01403
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 0.1400 0.21212 0.2642 0.34259
Specificity 0.8019 0.79936 0.7296 0.65574
Pos Pred Value 0.1842 0.25000 0.2523 0.26056
Neg Pred Value 0.7448 0.76292 0.7417 0.73801
Prevalence 0.2421 0.23971 0.2567 0.26150
Detection Rate 0.0339 0.05085 0.0678 0.08959
Detection Prevalence 0.1840 0.20339 0.2688 0.34383
Balanced Accuracy 0.4710 0.50574 0.4969 0.49917
stats_class_lrmulti <- data.frame(model = "LRmulti",
precision = conf_mat_lrmulti$overall["Accuracy"],
FN = conf_mat_lrmulti$table[2,1],
FP = conf_mat_lrmulti$table[1,2],
error.rate = 1 - conf_mat_lrmulti$overall["Accuracy"],
kappa = conf_mat_lrmulti$overall["Kappa"],
sensibilidad = mean(conf_mat_lrmulti$byClass[,"Sensitivity"]),
especificidad = mean(conf_mat_lrmulti$byClass[,"Specificity"]),
precisión = mean(conf_mat_lrmulti$byClass[,"Pos Pred Value"]),
recuperación = mean(conf_mat_lrmulti$byClass[,"Recall"]),
f.medida = mean(conf_mat_lrmulti$byClass[,"F1"])
)
stats_class_lrmulti
model precision FN FP error.rate kappa sensibilidad
Accuracy LRmulti 0.2421308 24 15 0.7578692 -0.01346912 0.2397162
especificidad precisión recuperación f.medida
Accuracy 0.7466648 0.2367565 0.2397162 0.2356659
library(keras)
library(mlr)
data_tn2 <- data_train
# Crear variables one-hot para la variable de salida
data_tn2$BH.staging.1 <- as.integer(data_tn2$BH.staging == "F1")
data_tn2$BH.staging.2 <- as.integer(data_tn2$BH.staging == "F2")
data_tn2$BH.staging.3 <- as.integer(data_tn2$BH.staging == "F3")
data_tn2$BH.staging.4 <- as.integer(data_tn2$BH.staging == "F4")
data_tn2 <- data_tn2 %>%
select(-BH.staging)
# Convertir a matriz y variables one-hot
nc <- ncol(data_tn2)
x_train <- as.matrix(data_tn2[, 1:nc])
y_train <- as.matrix(data_tn2[, c("BH.staging.1", "BH.staging.2", "BH.staging.3", "BH.staging.4")])
# Crear modelo secuencial
modelo_sfg <- keras_model_sequential() %>%
layer_dense(units = 128, activation = "relu", input_shape = nc) %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 64, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 32, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 16, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 4, activation = "softmax")
# Compilar modelo
#learning_rate <- c(0.001, 0.01, 0.1)
learning_rate <- 0.01
modelo_sfg %>% compile(
optimizer = optimizer_adam(learning_rate),
loss = "categorical_crossentropy",
metrics = "accuracy"
)
# Entrenar el modelo
history <- modelo_sfg %>% fit(
x = x_train,
y = y_train,
epochs = 100,
batch_size = 32,
validation_split = 0.2,
verbose = 0
)
summary(modelo_sfg)
Model: "sequential"
________________________________________________________________________________
Layer (type) Output Shape Param #
================================================================================
dense_4 (Dense) (None, 128) 2560
dropout_3 (Dropout) (None, 128) 0
dense_3 (Dense) (None, 64) 8256
dropout_2 (Dropout) (None, 64) 0
dense_2 (Dense) (None, 32) 2080
dropout_1 (Dropout) (None, 32) 0
dense_1 (Dense) (None, 16) 528
dropout (Dropout) (None, 16) 0
dense (Dense) (None, 4) 68
================================================================================
Total params: 13,492
Trainable params: 13,492
Non-trainable params: 0
________________________________________________________________________________
data_tt2 <- data_test
# Crear variables one-hot para la variable de salida
data_tt2$BH.staging.1 <- as.integer(data_tt2$BH.staging == "F1")
data_tt2$BH.staging.2 <- as.integer(data_tt2$BH.staging == "F2")
data_tt2$BH.staging.3 <- as.integer(data_tt2$BH.staging == "F3")
data_tt2$BH.staging.4 <- as.integer(data_tt2$BH.staging == "F4")
data_tt2 <- data_tt2 %>%
select(-BH.staging)
x_test <- as.matrix(data_tt2[, 1:nc])
predicciones_sfg_prob <- predict(modelo_sfg, x_test)
predicciones_sfg <- max.col(predicciones_sfg_prob)
# Convertir predicciones a valores originales de BH.staging
predicciones_sfg <- factor(ifelse(predicciones_sfg == 1, "F1",
ifelse(predicciones_sfg == 2, "F2",
ifelse(predicciones_sfg == 3, "F3", "F4"))),
levels = c("F1", "F2", "F3", "F4"))
conf_mat_sfg <- caret::confusionMatrix(predicciones_sfg, factor(data_test$BH.staging, levels = c("F1", "F2", "F3", "F4")))
conf_mat_sfg
Confusion Matrix and Statistics
Reference
Prediction F1 F2 F3 F4
F1 100 0 0 0
F2 0 99 0 0
F3 0 0 106 0
F4 0 0 0 108
Overall Statistics
Accuracy : 1
95% CI : (0.9911, 1)
No Information Rate : 0.2615
P-Value [Acc > NIR] : < 2.2e-16
Kappa : 1
Mcnemar's Test P-Value : NA
Statistics by Class:
Class: F1 Class: F2 Class: F3 Class: F4
Sensitivity 1.0000 1.0000 1.0000 1.0000
Specificity 1.0000 1.0000 1.0000 1.0000
Pos Pred Value 1.0000 1.0000 1.0000 1.0000
Neg Pred Value 1.0000 1.0000 1.0000 1.0000
Prevalence 0.2421 0.2397 0.2567 0.2615
Detection Rate 0.2421 0.2397 0.2567 0.2615
Detection Prevalence 0.2421 0.2397 0.2567 0.2615
Balanced Accuracy 1.0000 1.0000 1.0000 1.0000
stats_class_sfg <- data.frame(model = "SFG",
precision = conf_mat_sfg$overall["Accuracy"],
FN = conf_mat_sfg$table[2,1],
FP = conf_mat_sfg$table[1,2],
error.rate = 1 - conf_mat_sfg$overall["Accuracy"],
kappa = conf_mat_sfg$overall["Kappa"],
sensibilidad = mean(conf_mat_sfg$byClass[, "Sensitivity"]),
especificidad = mean(conf_mat_sfg$byClass[, "Specificity"]),
precisión = mean(conf_mat_sfg$byClass[, "Pos Pred Value"]),
recuperación = mean(conf_mat_sfg$byClass[, "Recall"]),
f.medida = mean(conf_mat_sfg$byClass[, "F1"])
)
stats_class_sfg
model precision FN FP error.rate kappa sensibilidad especificidad
Accuracy SFG 1 0 0 0 1 1 1
precisión recuperación f.medida
Accuracy 1 1 1
# Tabla resumen del rendimiento de los diferentes modelos:
stats_resumen <- rbind(stats_class_knn,
stats_class_nb,
stats_class_mlp,
stats_class_svmlineal,
stats_class_svmPoly,
stats_class_svmRadial,
stats_class_C5.0Tree,
stats_class_C5.0,
stats_class_J48,
stats_class_rf,
stats_class_lrqda,
stats_class_lrmulti,
stats_class_sfg)
# Ordenamos la tabla por la precisión y lo guardamos
stats_models_prec <- stats_resumen %>% arrange(desc(precision))
knitr::kable(stats_models_prec, digits = 3, caption = "Métricas del rendimiento de los modelos de aprendizaje automático.")
| model | precision | FN | FP | error.rate | kappa | sensibilidad | especificidad | precisión | recuperación | f.medida | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Accuracy12 | SFG | 1.000 | 0 | 0 | 0.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| Accuracy7 | C5.0 | 0.281 | 27 | 26 | 0.719 | 0.041 | 0.279 | 0.760 | 0.280 | 0.279 | 0.279 |
| Accuracy8 | J48 | 0.274 | 22 | 26 | 0.726 | 0.032 | 0.274 | 0.758 | 0.274 | 0.274 | 0.273 |
| Accuracy5 | SVMradial | 0.266 | 3 | 7 | 0.734 | 0.012 | 0.258 | 0.753 | 0.243 | 0.258 | 0.212 |
| Accuracy | KNN | 0.262 | 24 | 15 | 0.738 | 0.014 | 0.261 | 0.753 | 0.261 | 0.261 | 0.258 |
| Accuracy2 | MLP | 0.259 | 1 | 0 | 0.741 | -0.003 | 0.248 | 0.749 | NaN | 0.248 | NA |
| Accuracy3 | SVMlineal | 0.252 | 32 | 10 | 0.748 | 0.000 | 0.249 | 0.750 | 0.245 | 0.249 | 0.235 |
| Accuracy1 | Naive Bayes | 0.245 | 30 | 12 | 0.755 | -0.009 | 0.243 | 0.748 | 0.231 | 0.243 | 0.228 |
| Accuracy6 | C5.0Tree | 0.242 | 17 | 21 | 0.758 | -0.012 | 0.242 | 0.747 | 0.243 | 0.242 | 0.243 |
| Accuracy9 | RF | 0.242 | 24 | 15 | 0.758 | -0.013 | 0.240 | 0.747 | 0.237 | 0.240 | 0.236 |
| Accuracy10 | lrqda | 0.242 | 24 | 15 | 0.758 | -0.013 | 0.240 | 0.747 | 0.237 | 0.240 | 0.236 |
| Accuracy11 | LRmulti | 0.242 | 24 | 15 | 0.758 | -0.013 | 0.240 | 0.747 | 0.237 | 0.240 | 0.236 |
| Accuracy4 | SVMpoly | 0.232 | 25 | 21 | 0.768 | -0.023 | 0.234 | 0.744 | 0.228 | 0.234 | 0.230 |